Autonomous vehicle control assessment and selection

ABSTRACT

According to certain aspects, a computer-implemented method for operating an autonomous or semi-autonomous vehicle may be provided. With the customer&#39;s permission, an identity of a vehicle operator may be identified and a vehicle operator profile may be retrieved. Operating data regarding autonomous operation features operating the vehicle may be received from vehicle-mounted sensors. When a request to disable an autonomous feature is received, a risk level for the autonomous feature is determined and compared with a driver behavior setting for the autonomous feature stored in the vehicle operator profile. Based upon the risk level comparison, the autonomous vehicle retains control of vehicle or the autonomous feature is disengaged depending upon which is the safer driver—the autonomous vehicle or the vehicle human occupant. As a result, unsafe disengagement of self-driving functionality for autonomous vehicles may be alleviated. Insurance discounts may be provided for autonomous vehicles having this safety functionality.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application No.62/079,533 (filed Nov. 13, 2014); U.S. Provisional Application No.62/103,831 (filed Jan. 15, 2015); U.S. Provisional Application No.62/103,836 (filed Jan. 15, 2015); U.S. Provisional Application No.62/103,838 (filed Jan. 15, 2015); U.S. Provisional Application No.62/103,840 (filed Jan. 15, 2015); U.S. Provisional Application No.62/103,855 (filed Jan. 15, 2015); U.S. Provisional Application No.62/103,856 (filed Jan. 15, 2015); U.S. Provisional Application No.62/103,891 (filed Jan. 15, 2015); U.S. Provisional Application No.62/103,893 (filed Jan. 15, 2015); U.S. Provisional Application No.62/103,895 (filed Jan. 15, 2015); U.S. Provisional Application No.62/103,907 (filed Jan. 15, 2015); U.S. Provisional Application No.62/103,911 (filed Jan. 15, 2015); and U.S. Provisional Application No.62/103,914 (filed Jan. 15, 2015). The entirety of each of the foregoingprovisional applications is incorporated by reference herein.

Additionally, the present application is related to co-pending U.S.patent application Ser. No. 14/934,326 (filed Nov. 6, 2015); co-pendingU.S. patent application Ser. No. 14/934,333 (filed Nov. 6, 2015);co-pending U.S. patent application Ser. No. 14/931,339 (filed Nov. 6,2015); co-pending U.S. patent application Ser. No. 14/934,343 (filedNov. 6, 2015); co-pending U.S. patent application Ser. No. 14/934,345(filed Nov. 6, 2015); co-pending U.S. patent application Ser. No.14/934,347 (filed Nov. 6, 2015); co-pending U.S. patent application Ser.No. 14/934,352 (filed Nov. 6, 2015); co-pending U.S. patent applicationSer. No. 14/934,355 (filed Nov. 6, 2015); co-pending U.S. patentapplication Ser. No. 14/934,357 (filed Nov. 6, 2015); co-pending U.S.patent application Ser. No. 14/934,361 (filed Nov. 6, 2015); co-pendingU.S. patent application Ser. No. 14/934,371 (filed Nov. 6, 2015);co-pending U.S. patent application Ser. No. 14/934,381 (filed Nov. 6,2015); co-pending U.S. patent application Ser. No. 14/934,385 (filedNov. 6, 2015); co-pending U.S. patent application Ser. No. 14/934,393(filed Nov. 6, 2015); co-pending U.S. patent application Ser. No.14/934,400 (filed Nov. 6, 2015); and co-pending U.S. patent applicationSer. No. 14/934,405 (filed Nov. 6, 2015).

FIELD

The present disclosure generally relates to systems and methods foroperating, monitoring, assessing, or insuring autonomous orsemi-autonomous vehicles.

BACKGROUND

Vehicles are typically operated by a human vehicle operator who controlsboth steering and motive controls. Operator error, inattention,inexperience, misuse, or distraction leads to many vehicle accidentseach year, resulting in injury and damage. Autonomous or semi-autonomousvehicles augment vehicle operators' information or replace vehicleoperators' control commands to operate the vehicle in whole or part withcomputer systems based upon information from sensors within the vehicle.

Vehicle or automobile insurance exists to provide financial protectionagainst physical damage and/or bodily injury resulting from trafficaccidents and against liability that could arise therefrom. Typically, acustomer purchases a vehicle insurance policy for a policy rate having aspecified term. In exchange for payments from the insured customer, theinsurer pays for damages to the insured which are caused by coveredperils, acts, or events as specified by the language of the insurancepolicy. The payments from the insured are generally referred to as“premiums,” and typically are paid on behalf of the insured over time atperiodic intervals. An insurance policy may remain “in-force” whilepremium payments are made during the term or length of coverage of thepolicy as indicated in the policy. An insurance policy may “lapse” (orhave a status or state of “lapsed”), for example, when premium paymentsare not being paid or if the insured or the insurer cancels the policy.

Premiums may be typically determined based upon a selected level ofinsurance coverage, location of vehicle operation, vehicle model, andcharacteristics or demographics of the vehicle operator. Thecharacteristics of a vehicle operator that affect premiums may includeage, years operating vehicles of the same class, prior incidentsinvolving vehicle operation, and losses reported by the vehicle operatorto the insurer or a previous insurer. Past and current premiumdetermination methods do not, however, account for use of autonomousvehicle operating features. The present embodiments may, inter alia,alleviate this and/or other drawbacks associated with conventionaltechniques.

BRIEF SUMMARY

The present embodiments may be related to autonomous or semi-autonomousvehicle functionality, including driverless operation, accidentavoidance, or collision warning systems. These autonomous vehicleoperation features may either assist the vehicle operator to more safelyor efficiently operate a vehicle or may take full control of vehicleoperation under some or all circumstances. The present embodiments mayalso facilitate risk assessment and premium determination for vehicleinsurance policies covering vehicles with autonomous operation features.For instance, a consumer may opt-in to a rewards program that rewardsthem, such as in the form of insurance discounts, for affirmativelysharing data related to their vehicles and/or autonomous features withan insurance provider.

In accordance with the described embodiments, the disclosure hereingenerally addresses systems and methods for determining to transferoperation of an autonomous or semi-autonomous vehicle between autonomousoperation features and a vehicle operator. A computer (such as anon-board computer, mobile device, or server communicatively connected tothe vehicle) associated with the vehicle may (1) determine an identityof a vehicle operator; (2) receive a vehicle operator profile associatedwith the vehicle operator; (3) receive operating data regarding one ormore autonomous operation features of the autonomous or semi-autonomousvehicle; (4) determine one or more autonomous operation risk levelsassociated with operation of the autonomous or semi-autonomous vehicleby the one or more autonomous operation features based upon (i) receivedoperating data, and/or (ii) driving behavior settings for the vehicleoperator that are pre-determined and/or stored in the vehicle operatorprofile; (5) determine one or more operator risk levels associated withoperation of the autonomous or semi-autonomous vehicle by the vehicleoperator based upon the received vehicle operating data and/or vehicleoperator profile (such as by comparing the vehicle operating data and/orcurrent environment conditions) with the vehicle operator profile); (6)determine to engage or disengage at least one of the one or moreautonomous operation features based upon the determine one or moreautonomous operation risk levels and the one or more operator risklevels; and/or (7) present an alert to the vehicle operator regardingengagement or disengagement of the at least one of the one or moreautonomous operation features.

Determining to disengage the at least one of the one or more autonomousoperation features may include determining that the one or moreautonomous operation risk levels associated with operation of theautonomous or semi-autonomous vehicle by the at least one of the one ormore autonomous operation features exceed the corresponding one or moreoperator risk levels associated with the same control functions of theautonomous or semi-autonomous vehicle as the at least one of the one ormore autonomous operation features, such that manual operation may besafer than autonomous operation under the conditions. Determining toengage the at least one of the one or more autonomous operation featuresmay include determining that the one or more operator risk levelsassociated with operation of the autonomous or semi-autonomous vehicleby the vehicle operator exceed the corresponding one or more autonomousoperation risk levels at least one of the one or more autonomousoperation features associated with the same control functions of theautonomous operation features of the autonomous or semi-autonomousvehicle, such that autonomous operation may be safer than manualoperation under the conditions. As a result, the vehicle control systemmay allow the safer driver—either the autonomous vehicle or humandriver/passenger/occupant—to remain or gain control of the vehicle.

The operating data may include data from one or more sensors disposedwithin the autonomous or semi-autonomous vehicle, which may include dataregarding the vehicle environment, such as weather, traffic, and/orconstruction. In some embodiments, the computer may receive autonomouscommunication data from one or more external sources, which may also beused to determine whether to disengage at least one of the one or moreautonomous operation features.

In some embodiments, the computer may further determine a preparednesslevel of the vehicle operator to assume control of one or more functionsof operating the autonomous or semi-autonomous vehicle controlled by theat least one of the one or more autonomous operation features, whichpreparedness level may be used to determine whether to disengage atleast one of the one or more autonomous operation features. When thepreparedness level of the vehicle operator is below a transferthreshold, the computer may cause at least one of the one or moreautonomous operation features not to disengage during operation of theautonomous or semi-autonomous vehicle. When the preparedness level isbelow the transfer threshold and above a minimum threshold, the alertmay be presented to the vehicle operator and/or the preparedness leveldetermined again after presentation of the alert. When the preparednesslevel is below a minimum threshold, the autonomous or semi-autonomousvehicle may discontinue operation. The computer may also cause theautonomous or semi-autonomous vehicle to discontinue operation when theautonomous operation risk levels exceed a critical risk threshold andthe preparedness level is below a transfer threshold.

In further embodiments, the computer may adjust one or more costsassociated with an insurance policy associated with the vehicleoperator. The adjustment may be based upon the determination todisengage the at least one of the one or more autonomous operationfeatures based upon the determined one or more autonomous operation risklevels and/or the one or more operator risk levels. The costs associatedwith the insurance policy may include one or more of the following: apremium, a discount, a surcharge, a rate level, a cost based upon adistance traveled, a cost based upon a vehicle trip, and/or a cost basedupon a duration of vehicle operation.

In each of the embodiments or aspects described above, the methods maybe provided in corresponding computer systems including at least one ormore processors and a non-transitory program memory coupled to the oneor more processors and storing executable instructions. The computersystems may further include or be communicatively connected to one ormore sensors, communication components or devices, or other equipment asdescribed herein. In yet another aspect, a tangible, non-transitorycomputer-readable medium storing instructions corresponding to each ofthe embodiments or aspects described above may be provided. Each of themethods or executable instructions of the computer systems orcomputer-readable media may include additional, fewer, or alternateactions, including those discussed elsewhere herein.

BRIEF DESCRIPTION OF THE DRAWINGS

Advantages will become more apparent to those skilled in the art fromthe following description of the preferred embodiments which have beenshown and described by way of illustration. As will be realized, thepresent embodiments may be capable of other and different embodiments,and their details are capable of modification in various respects.Accordingly, the drawings and description are to be regarded asillustrative in nature and not as restrictive.

The figures described below depict various aspects of the applications,methods, and systems disclosed herein. It should be understood that eachfigure depicts an embodiment of a particular aspect of the disclosedapplications, systems and methods, and that each of the figures isintended to accord with a possible embodiment thereof. Furthermore,wherever possible, the following description refers to the referencenumerals included in the following figures, in which features depictedin multiple figures are designated with consistent reference numerals.

FIG. 1 illustrates a block diagram of an exemplary computer network, acomputer server, a mobile device, and an on-board computer forimplementing autonomous vehicle operation, monitoring, evaluation, andinsurance processes in accordance with the described embodiments;

FIG. 2 illustrates a block diagram of an exemplary on-board computer ormobile device;

FIG. 3 illustrates a flow diagram of an exemplary autonomous vehicleoperation method in accordance with the presently described embodiments;

FIG. 4 illustrates a flow diagram of an exemplary monitoring methodduring vehicle operation in accordance with the presently describedembodiments;

FIG. 5 illustrates a flow diagram of an exemplary operating statusassessment method in accordance with the presently describedembodiments;

FIG. 6 illustrates a flow diagram of an exemplary operating statusmonitoring method in accordance with the presently describedembodiments;

FIGS. 7A-B illustrate flow diagrams depicting exemplary vehicleoperation hand-off methods in accordance with the presently describedembodiments;

FIG. 8 illustrates a flow diagram depicting an exemplary vehicleoperator identification method in accordance with the presentlydescribed embodiments;

FIG. 9 illustrates a flow diagram depicting an exemplary vehicleoperator use monitoring and evaluation method in accordance with thepresently described embodiments;

FIG. 10 illustrates a flow diagram depicting an exemplary costcomparison method in accordance with the presently describedembodiments; and

FIG. 11 illustrates a flow diagram depicting an exemplary autonomousoperation feature update method in accordance with the presentlydescribed embodiments;

FIG. 12 illustrates a flow diagram depicting an exemplary autonomousvehicle repair method in accordance with the presently describedembodiments; and

FIG. 13 illustrates a flow diagram depicting an exemplary infrastructurecommunication method in accordance with the presently describedembodiments.

DETAILED DESCRIPTION

The systems and methods disclosed herein generally relate to evaluating,monitoring, and managing risks related to the operation of autonomous orsemi-autonomous vehicles having autonomous (or semi-autonomous)operation features. The systems and methods further relate to pricingand processing vehicle insurance policies for autonomous orsemi-autonomous vehicles. The autonomous operation features may takefull control of the vehicle under certain conditions, viz. fullyautonomous operation, or the autonomous operation features may assistthe vehicle operator in operating the vehicle, viz. partially autonomousoperation. Fully autonomous operation features may include systemswithin the vehicle that pilot the vehicle to a destination with orwithout a vehicle operator present (e.g., an operating system for adriverless car). Partially autonomous operation features may assist thevehicle operator in limited ways (e.g., automatic braking or collisionavoidance systems).

The type and quality of the autonomous operation features may affect therisks related to operating a vehicle, both individually and/or incombination. In addition, configurations and settings of the autonomousoperation features may further impact the risks. To account for theeffects on such risks, some embodiments evaluate the quality of eachautonomous operation feature and/or combination of features. Additionalembodiments evaluate the risks associated with the vehicle operatorinteracting with the autonomous operation features. Further embodimentsaddress the relative risks associated with control of some aspects ofvehicle control by the autonomous operation features or by the vehicleoperator. Still further embodiments address use of information receivedor generated by the autonomous operation features to manage risk and/ordamage.

Some autonomous operation features may be adapted for use underparticular conditions, such as city driving or highway driving.Additionally, the vehicle operator may be able to configure settingsrelating to the features or may enable or disable the featuresindividually or in groups. For example, the vehicle operator may selecta mode of operation for the autonomous or semi-autonomous vehicle, whichmay adjust settings for one or more autonomous operation features.Therefore, some embodiments monitor use of the autonomous operationfeatures, which may include the settings or levels of feature use duringvehicle operation, as well as the selection of features or settings ofthe autonomous operation features chosen by the vehicle operator.

Information obtained by monitoring feature usage may be used todetermine risk levels associated with vehicle operation, eithergenerally or in relation to a vehicle operator. In such situations,total risk may be determined by a weighted combination of the risklevels associated with operation while autonomous operation features areenabled (with relevant settings) and the risk levels associated withoperation while autonomous operation features are disabled. For fullyautonomous vehicles, settings or configurations relating to vehicleoperation may be monitored and used in determining vehicle operatingrisk.

In addition to use in controlling the vehicle, information regarding therisks associated with vehicle operation with and without the autonomousoperation features may then be used to determine risk categories orpremiums for a vehicle insurance policy covering a vehicle withautonomous operation features. Risk category or price may be determinedbased upon factors relating to the evaluated effectiveness of theautonomous vehicle features. The risk or price determination may alsoinclude traditional factors, such as location, vehicle type, and levelof vehicle use. For fully autonomous vehicles, factors relating tovehicle operators may be excluded entirely. For partially autonomousvehicles, factors relating to vehicle operators may be reduced inproportion to the evaluated effectiveness and monitored usage levels ofthe autonomous operation features. For vehicles with autonomouscommunication features that obtain information from external sources(e.g., other vehicles or infrastructure), the risk level and/or pricedetermination may also include an assessment of the availability ofexternal sources of information. Location and/or timing of vehicle usemay thus be monitored and/or weighted to determine the risk associatedwith operation of the vehicle.

Autonomous Automobile Insurance

The present embodiments may relate to assessing and pricing insurancebased upon autonomous (or semi-autonomous) functionality of a vehicle,utilization of the autonomous (or semi-autonomous) functionality of thevehicle, and/or operation of the vehicle by a human operator. In someembodiments, the vehicle operator may not control the operations of thevehicle directly, in which case the assessment, rating, and pricing ofinsurance may exclude consideration of the vehicle operator. A smartvehicle may maneuver itself without human intervention and/or includesensors, processors, computer instructions, and/or other components thatmay perform or direct certain actions conventionally performed by ahuman operator.

An analysis of how artificial intelligence facilitates avoidingaccidents and/or mitigates the severity of accidents may be used tobuild a database and/or model of risk assessment. After which,automobile insurance risk and/or premiums (as well as insurancediscounts, rewards, and/or points) may be adjusted based upon autonomousor semi-autonomous vehicle functionality, such as by groups ofautonomous or semi-autonomous functionality or individual features. Inone aspect, an evaluation may be performed on how artificialintelligence, and the usage thereof, impacts automobile accidents and/orautomobile insurance claims.

The types of autonomous or semi-autonomous vehicle-related functionalityor technology that may be used with the present embodiments to replacehuman driver actions may include and/or be related to the followingtypes of functionality: (a) fully autonomous (driverless); (b) limiteddriver control; (c) vehicle-to-vehicle (V2V) wireless communication; (d)vehicle-to-infrastructure (and/or vice versa) wireless communication;(e) automatic or semi-automatic steering; (f) automatic orsemi-automatic acceleration; (g) automatic or semi-automatic braking;(h) automatic or semi-automatic blind spot monitoring; (i) automatic orsemi-automatic collision warning; (j) adaptive cruise control; (k)automatic or semi-automatic parking/parking assistance; (l) automatic orsemi-automatic collision preparation (windows roll up, seat adjustsupright, brakes pre-charge, etc.); (m) driver acuity/alertnessmonitoring; (n) pedestrian detection; (o) autonomous or semi-autonomousbackup systems; (p) road mapping systems; (q) software security andanti-hacking measures; (r) theft prevention/automatic return; (s)automatic or semi-automatic driving without occupants; and/or otherfunctionality. Additionally or alternatively, the autonomous orsemi-autonomous functionality or technology may include and/or may berelated to: (t) driver alertness or responsive monitoring; (u)pedestrian detection; (v) artificial intelligence and/or back-upsystems; (w) navigation or GPS-related systems; (x) security and/oranti-hacking measures; and/or (y) theft prevention systems.

The adjustments to automobile insurance rates or premiums based upon theautonomous or semi-autonomous vehicle-related functionality ortechnology may take into account the impact of such functionality ortechnology on the likelihood of a vehicle accident or collisionoccurring. For instance, a processor may analyze historical accidentinformation and/or test data involving vehicles having autonomous orsemi-autonomous functionality. Factors that may be analyzed and/oraccounted for that are related to insurance risk, accident information,or test data may include (1) point of impact; (2) type of road; (3) timeof day; (4) weather conditions; (5) road construction; (6) type/lengthof trip; (7) vehicle style; (8) level of pedestrian traffic; (9) levelof vehicle congestion; (10) atypical situations (such as manual trafficsignaling); (11) availability of internet connection for the vehicle;and/or other factors. These types of factors may also be weightedaccording to historical accident information, predicted accidents,vehicle trends, test data, and/or other considerations.

In one aspect, the benefit of one or more autonomous or semi-autonomousfunctionalities or capabilities may be determined, weighted, and/orotherwise characterized. For instance, the benefit of certain autonomousor semi-autonomous functionality may be substantially greater in city orcongested traffic, as compared to open road or country driving traffic.Additionally or alternatively, certain autonomous or semi-autonomousfunctionality may only work effectively below a certain speed, e.g.,during city driving or driving in congestion. Other autonomous orsemi-autonomous functionality may operate more effectively on thehighway and away from city traffic, such as cruise control. Furtherindividual autonomous or semi-autonomous functionality may be impactedby weather, such as rain or snow, and/or time of day (day light versusnight). As an example, fully automatic or semi-automatic lane detectionwarnings may be impacted by rain, snow, ice, and/or the amount ofsunlight (all of which may impact the imaging or visibility of lanemarkings painted onto a road surface, and/or road markers or streetsigns).

Automobile insurance premiums, rates, discounts, rewards, refunds,points, or other costs may be adjusted based upon the percentage of timeor vehicle usage that the vehicle is the driver, i.e., the amount oftime a specific driver uses each type of autonomous (or evensemi-autonomous) vehicle functionality. Such premiums, rates, discounts,rewards, refunds, points, or other costs may further be adjusted basedupon the extent of use of the autonomous operation features, includingsettings or modes impacting the operation of the autonomous operationfeatures. Moreover, information regarding the vehicle environment duringuse (e.g., weather, traffic, time of day, etc.) may be included ininsurance adjustment determinations, as may traditional informationregarding one or more vehicle operators (and the extent to which eachvehicle operator uses the vehicle).

Such usage information for a particular vehicle may be gathered overtime and/or via remote wireless communication with the vehicle. Oneembodiment may involve a processor on the vehicle, such as within avehicle control system or dashboard, monitoring in real-time the vehicleoperator and/or the use of autonomous operation features while thevehicle is operating. Other types of monitoring may be remotelyperformed, such as via wireless communication between the vehicle and aremote server, or wireless communication between a vehicle-mounteddedicated device (that is configured to gather autonomous orsemi-autonomous functionality usage information) and a remote server.

Additionally, in some embodiments, the vehicle may transmit and/orreceive communications to or from external sources, such as othervehicles (V2V), infrastructure (e.g., a bridge, traffic light, railroadcrossing, toll both, marker, sign, or other equipment along the side ofa road or highway), pedestrians, databases, or other information sourcesexternal to the vehicle. Such communication may allow the vehicle toobtain information regarding other vehicles, obstacles, road conditions,or environmental conditions that could not be detected by sensorsdisposed within the vehicle. For example, V2V communication may allow avehicle to identify other vehicles approaching an intersection even whenthe direct line between the vehicle and the other vehicles is obscuredby buildings. As another example, the V2V wireless communication from afirst vehicle to a second vehicle (following the first vehicle) mayindicate that the first vehicle is braking, which may include the degreeto which the vehicle is braking. In response, the second vehicle mayautomatically or autonomously brake in advance of detecting thedeceleration of the first vehicle based upon sensor data.

Insurance premiums, rates, ratings, discounts, rewards, special offers,points, programs, refunds, claims, claim amounts, or other costsassociated with an insurance policy may be adjusted for, or mayotherwise take into account, the foregoing functionality and/or theother functionality described herein. For instance, insurance policiesmay be updated based upon installed autonomous operation features, theextent of use of the autonomous operation features, V2V wirelesscommunication, and/or vehicle-to-infrastructure orinfrastructure-to-vehicle wireless communication. The presentembodiments may assess and price insurance risks at least in part basedupon autonomous operation features that replace some actions of thevehicle operator in controlling the vehicle, including settings andoperating status of the autonomous operation features.

Exemplary Autonomous Vehicle Operation System

FIG. 1 illustrates a block diagram of an exemplary autonomous vehicleinsurance system 100 on which the exemplary methods described herein maybe implemented. The high-level architecture includes both hardware andsoftware applications, as well as various data communications channelsfor communicating data between the various hardware and softwarecomponents. The autonomous vehicle insurance system 100 may be roughlydivided into front-end components 102 and back-end components 104. Thefront-end components 102 may obtain information regarding a vehicle 108(e.g., a car, truck, motorcycle, etc.) and the surrounding environment.An on-board computer 114 may utilize this information to operate thevehicle 108 according to an autonomous operation feature or to assistthe vehicle operator in operating the vehicle 108. To monitor thevehicle 108, the front-end components 102 may include one or moresensors 120 installed within the vehicle 108 that may communicate withthe on-board computer 114. The front-end components 102 may furtherprocess the sensor data using the on-board computer 114 or a mobiledevice 110 (e.g., a smart phone, a tablet computer, a special purposecomputing device, etc.) to determine when the vehicle is in operationand information regarding the vehicle. In some embodiments of the system100, the front-end components 102 may communicate with the back-endcomponents 104 via a network 130. Either the on-board computer 114 orthe mobile device 110 may communicate with the back-end components 104via the network 130 to allow the back-end components 104 to recordinformation regarding vehicle usage. The back-end components 104 may useone or more servers 140 to receive data from the front-end components102, determine use and effectiveness of autonomous operation features,determine risk levels or premium price, and/or facilitate purchase orrenewal of an autonomous vehicle insurance policy.

The front-end components 102 may be disposed within or communicativelyconnected to one or more on-board computers 114, which may bepermanently or removably installed in the vehicle 108. The on-boardcomputer 114 may interface with the one or more sensors 120 within thevehicle 108 (e.g., an ignition sensor, an odometer, a system clock, aspeedometer, a tachometer, an accelerometer, a gyroscope, a compass, ageolocation unit, a camera, a distance sensor, etc.), which sensors mayalso be incorporated within or connected to the on-board computer 114.The front-end components 102 may further include a communicationcomponent 122 to transmit information to and receive information fromexternal sources, including other vehicles, infrastructure, or theback-end components 104. In some embodiments, the mobile device 110 maysupplement the functions performed by the on-board computer 114described herein by, for example, sending or receiving information toand from the mobile server 140 via the network 130. In otherembodiments, the on-board computer 114 may perform all of the functionsof the mobile device 110 described herein, in which case no mobiledevice 110 may be present in the system 100. Either or both of themobile device 110 or on-board computer 114 may communicate with thenetwork 130 over links 112 and 118, respectively. Additionally, themobile device 110 and on-board computer 114 may communicate with oneanother directly over link 116.

The mobile device 110 may be either a general-use personal computer,cellular phone, smart phone, tablet computer, phablet, wearableelectronics, PDA (personal digital assistant), smart glasses, smartwatches, smart bracelet, pager, computing device configured for wired orwireless RF (radio frequency) communication, a dedicated vehicle usemonitoring device, and/or other mobile computing device. Although onlyone mobile device 110 is illustrated, it should be understood that aplurality of mobile devices 110 may be used in some embodiments. Theon-board computer 114 may be a general-use on-board computer capable ofperforming many functions relating to vehicle operation or a dedicatedcomputer for autonomous vehicle operation. Further, the on-boardcomputer 114 may be installed by the manufacturer of the vehicle 108 oras an aftermarket modification or addition to the vehicle 108. In someembodiments or under certain conditions, the mobile device 110 oron-board computer 114 may function as thin-client devices that outsourcesome or most of the processing to the server 140.

The sensors 120 may be removably or fixedly installed within the vehicle108 and may be disposed in various arrangements to provide informationto the autonomous operation features. Among the sensors 120 may beincluded one or more of a GPS (Global Positioning System) unit, othersatellite-based navigation unit, a radar unit, a LIDAR (Light Detectionand Ranging) unit, an ultrasonic sensor, an infrared sensor, a camera,an accelerometer, a tachometer, and/or a speedometer. Some of thesensors 120 (e.g., radar, LIDAR, or camera units) may actively orpassively scan the vehicle environment for obstacles (e.g., othervehicles, buildings, pedestrians, etc.), lane markings, or signs orsignals. Other sensors 120 (e.g., GPS, accelerometer, or tachometerunits) may provide data for determining the location or movement of thevehicle 108. Other sensors 120 may be directed to the interior orpassenger compartment of the vehicle 108, such as cameras, microphones,pressure sensors, thermometers, or similar sensors to monitor thevehicle operator and/or passengers within the vehicle 108. Informationgenerated or received by the sensors 120 may be communicated to theon-board computer 114 or the mobile device 110 for use in autonomousvehicle operation.

In some embodiments, the communication component 122 may receiveinformation from external sources, such as other vehicles orinfrastructure. The communication component 122 may also sendinformation regarding the vehicle 108 to external sources. To send andreceive information, the communication component 122 may include atransmitter and a receiver designed to operate according topredetermined specifications, such as the dedicated short-rangecommunication (DSRC) channel, wireless telephony, Wi-Fi, or otherexisting or later-developed communications protocols. The receivedinformation may supplement the data received from the sensors 120 toimplement the autonomous operation features. For example, thecommunication component 122 may receive information that an autonomousvehicle ahead of the vehicle 108 is reducing speed, allowing theadjustments in the autonomous operation of the vehicle 108.

In further embodiments, the front-end components may include aninfrastructure communication device 124 for monitoring the status of oneor more infrastructure components 126. The infrastructure communicationdevice 124 may include or be communicatively connected to one or moresensors (not shown) for detecting information relating to the conditionof the infrastructure component 126. The sensors (not shown) maygenerate data relating to weather conditions, traffic conditions, oroperating status of the infrastructure component 126. The infrastructurecommunication device 124 may be configured to receive the sensor datagenerated and determine a condition of the infrastructure component 126,such as weather conditions, road integrity, construction, traffic,available parking spaces, etc. The infrastructure communication device124 may further be configured to communicate information to vehicles 108via the communication component 122. In some embodiments, theinfrastructure communication device 124 may receive information from thevehicles 108, while, in other embodiments, the infrastructurecommunication device 124 may only transmit information to the vehicles108.

In addition to receiving information from the sensors 120, the on-boardcomputer 114 may directly or indirectly control the operation of thevehicle 108 according to various autonomous operation features. Theautonomous operation features may include software applications orroutines implemented by the on-board computer 114 to control thesteering, braking, or throttle of the vehicle 108. To facilitate suchcontrol, the on-board computer 114 may be communicatively connected tothe controls or components of the vehicle 108 by various electrical orelectromechanical control components (not shown). In embodimentsinvolving fully autonomous vehicles, the vehicle 108 may be operableonly through such control components (not shown). In other embodiments,the control components may be disposed within or supplement othervehicle operator control components (not shown), such as steeringwheels, accelerator or brake pedals, or ignition switches.

In some embodiments, the front-end components 102 may communicate withthe back-end components 104 via the network 130. The network 130 may bea proprietary network, a secure public internet, a virtual privatenetwork or some other type of network, such as dedicated access lines,plain ordinary telephone lines, satellite links, cellular data networks,combinations of these. Where the network 130 comprises the Internet,data communications may take place over the network 130 via an Internetcommunication protocol.

The back-end components 104 may include one or more servers 140. Eachserver 140 may include one or more computer processors adapted andconfigured to execute various software applications and components ofthe autonomous vehicle insurance system 100, in addition to othersoftware applications. The server 140 may further include a database146, which may be adapted to store data related to the operation of thevehicle 108 and its autonomous operation features. Such data mightinclude, for example, dates and times of vehicle use, duration ofvehicle use, use and settings of autonomous operation features, speed ofthe vehicle 108, RPM or other tachometer readings of the vehicle 108,lateral and longitudinal acceleration of the vehicle 108, incidents ornear collisions of the vehicle 108, communication between the autonomousoperation features and external sources, environmental conditions ofvehicle operation (e.g., weather, traffic, road condition, etc.), errorsor failures of autonomous operation features, or other data relating touse of the vehicle 108 and the autonomous operation features, which maybe uploaded to the server 140 via the network 130. The server 140 mayaccess data stored in the database 146 when executing various functionsand tasks associated with the evaluating feature effectiveness orassessing risk relating to an autonomous vehicle.

Although the autonomous vehicle insurance system 100 is shown to includeone vehicle 108, one mobile device 110, one on-board computer 114, andone server 140, it should be understood that different numbers ofvehicles 108, mobile devices 110, on-board computers 114, and/or servers140 may be utilized. For example, the system 100 may include a pluralityof servers 140 and hundreds of mobile devices 110 or on-board computers114, all of which may be interconnected via the network 130.Furthermore, the database storage or processing performed by the one ormore servers 140 may be distributed among a plurality of servers 140 inan arrangement known as “cloud computing.” This configuration mayprovide various advantages, such as enabling near real-time uploads anddownloads of information as well as periodic uploads and downloads ofinformation. This may in turn support a thin-client embodiment of themobile device 110 or on-board computer 114 discussed herein.

The server 140 may have a controller 155 that is operatively connectedto the database 146 via a link 156. It should be noted that, while notshown, additional databases may be linked to the controller 155 in aknown manner. For example, separate databases may be used for autonomousoperation feature information, vehicle insurance policy information, andvehicle use information. The controller 155 may include a program memory160, a processor 162 (which may be called a microcontroller or amicroprocessor), a random-access memory (RAM) 164, and an input/output(I/O) circuit 166, all of which may be interconnected via anaddress/data bus 165. It should be appreciated that although only onemicroprocessor 162 is shown, the controller 155 may include multiplemicroprocessors 162. Similarly, the memory of the controller 155 mayinclude multiple RAMs 164 and multiple program memories 160. Althoughthe I/O circuit 166 is shown as a single block, it should be appreciatedthat the I/O circuit 166 may include a number of different types of I/Ocircuits. The RAM 164 and program memories 160 may be implemented assemiconductor memories, magnetically readable memories, or opticallyreadable memories, for example. The controller 155 may also beoperatively connected to the network 130 via a link 135.

The server 140 may further include a number of software applicationsstored in a program memory 160. The various software applications on theserver 140 may include an autonomous operation information monitoringapplication 141 for receiving information regarding the vehicle 108 andits autonomous operation features, a feature evaluation application 142for determining the effectiveness of autonomous operation features undervarious conditions, a compatibility evaluation application 143 fordetermining the effectiveness of combinations of autonomous operationfeatures, a risk assessment application 144 for determining a riskcategory associated with an insurance policy covering an autonomousvehicle, and an autonomous vehicle insurance policy purchase application145 for offering and facilitating purchase or renewal of an insurancepolicy covering an autonomous vehicle. The various software applicationsmay be executed on the same computer processor or on different computerprocessors.

The various software applications may include various software routinesstored in the program memory 160 to implement various modules using theprocess 162. Additionally, or alternatively, the software applicationsor routines may interact with various hardware modules that may beinstalled within or connected to the server 140. Such modules mayimplement part of all of the various exemplary methods discussed hereinor other related embodiments. Such modules may include a vehicle controlmodule for determining and implementing control decisions to operate thevehicle 108, a system status module for determining the operating statusof autonomous operation features, a monitoring module for monitoring theoperation of the vehicle 108, a remediation module for correctingabnormal operating states of autonomous operation features, an insurancemodule for determining risks and costs associated with operation of thevehicle 108, an alert module for generating and presenting alertsregarding the vehicle 108 or the vehicle operator, a risk assessmentmodule for determining risks associated with operation of the vehicle108 by the autonomous operation features or by the vehicle operator, anidentification module for identifying or verifying the identity of thevehicle operator, an information module for obtaining informationregarding a vehicle operator or vehicle 108, a use cost module fordetermining costs associated with operation of the vehicle 108, acomparison module for comparing one or more costs associated with owningor operating the vehicle 108, an update module for updating anautonomous operation feature of the vehicle 108, or other modules.

Exemplary Mobile Device or on-Board Computer

FIG. 2 illustrates a block diagram of an exemplary mobile device 110and/or an exemplary on-board computer 114 consistent with the system100. The mobile device 110 and/or on-board computer 114 may include adisplay 202, a GPS unit 206, a communication unit 220, an accelerometer224, one or more additional sensors (not shown), a user-input device(not shown), and/or, like the server 140, a controller 204. In someembodiments, the mobile device 110 and on-board computer 114 may beintegrated into a single device, or either may perform the functions ofboth. The on-board computer 114 (or mobile device 110) may interfacewith the sensors 120 to receive information regarding the vehicle 108and its environment, which information may be used by the autonomousoperation features to operate the vehicle 108.

Similar to the controller 155, the controller 204 may include a programmemory 208, one or more microcontrollers or microprocessors (MP) 210, aRAM 212, and an I/O circuit 216, all of which are interconnected via anaddress/data bus 214. The program memory 208 may include an operatingsystem 226, a data storage 228, a plurality of software applications230, and/or a plurality of software routines 240. The operating system226, for example, may include one of a plurality of general purpose ormobile platforms, such as the Android™, iOS®, or Windows® systems,developed by Google Inc., Apple Inc., and Microsoft Corporation,respectively. Alternatively, the operating system 226 may be a customoperating system designed for autonomous vehicle operation using theon-board computer 114. The data storage 228 may include data such asuser profiles and preferences, application data for the plurality ofapplications 230, routine data for the plurality of routines 240, andother data related to the autonomous operation features. In someembodiments, the controller 204 may also include, or otherwise becommunicatively connected to, other data storage mechanisms (e.g., oneor more hard disk drives, optical storage drives, solid state storagedevices, etc.) that reside within the vehicle 108.

As discussed with reference to the controller 155, it should beappreciated that although FIG. 2 depicts only one microprocessor 210,the controller 204 may include multiple microprocessors 210. Similarly,the memory of the controller 204 may include multiple RAMs 212 andmultiple program memories 208. Although FIG. 2 depicts the I/O circuit216 as a single block, the I/O circuit 216 may include a number ofdifferent types of I/O circuits. The controller 204 may implement theRAMs 212 and the program memories 208 as semiconductor memories,magnetically readable memories, or optically readable memories, forexample.

The one or more processors 210 may be adapted and configured to executeany of one or more of the plurality of software applications 230 or anyone or more of the plurality of software routines 240 residing in theprogram memory 204, in addition to other software applications. One ofthe plurality of applications 230 may be an autonomous vehicle operationapplication 232 that may be implemented as a series of machine-readableinstructions for performing the various tasks associated withimplementing one or more of the autonomous operation features accordingto the autonomous vehicle operation method 300. Another of the pluralityof applications 230 may be an autonomous communication application 234that may be implemented as a series of machine-readable instructions fortransmitting and receiving autonomous operation information to or fromexternal sources via the communication unit 220. Still anotherapplication of the plurality of applications 230 may include anautonomous operation monitoring application 236 that may be implementedas a series of machine-readable instructions for sending informationregarding autonomous operation of the vehicle to the server 140 via thenetwork 130.

The plurality of software applications 230 may call various of theplurality of software routines 240 to perform functions relating toautonomous vehicle operation, monitoring, or communication. In someembodiments, the plurality of software routines may further assess risklevels or determine insurance policy costs and adjustments. One of theplurality of software routines 240 may be a configuration routine 242 toreceive settings from the vehicle operator to configure the operatingparameters of an autonomous operation feature. Another of the pluralityof software routines 240 may be a sensor control routine 244 to transmitinstructions to a sensor 120 and receive data from the sensor 120. Stillanother of the plurality of software routines 240 may be an autonomouscontrol routine 246 that performs a type of autonomous control, such ascollision avoidance, lane centering, and/or speed control. In someembodiments, the autonomous vehicle operation application 232 may causea plurality of autonomous control routines 246 to determine controlactions required for autonomous vehicle operation. Similarly, one of theplurality of software routines 240 may be a monitoring and reportingroutine 248 that monitors and transmits information regarding autonomousvehicle operation to the server 140 via the network 130. Yet another ofthe plurality of software routines 240 may be an autonomouscommunication routine 250 for receiving and transmitting informationbetween the vehicle 108 and external sources to improve theeffectiveness of the autonomous operation features.

Any of the plurality of software routines 240 may be designed to operateindependently of the software applications 230 or in conjunction withthe software applications 230 to implement modules associated with themethods discussed herein using the microprocessor 210 of the controller204. Additionally, or alternatively, the software applications 230 orsoftware routines 240 may interact with various hardware modules thatmay be installed within or connected to the mobile device 110 or theon-board computer 114. Such modules may implement part of all of thevarious exemplary methods discussed herein or other related embodiments.

For instance, such modules may include a vehicle control module fordetermining and implementing control decisions to operate the vehicle108, a system status module for determining the operating status ofautonomous operation features, a monitoring module for monitoring theoperation of the vehicle 108, a remediation module for correctingabnormal operating states of autonomous operation features, an insurancemodule for determining risks and costs associated with operation of thevehicle 108, an alert module for generating and presenting alertsregarding the vehicle 108 or the vehicle operator, a risk assessmentmodule for determining risks associated with operation of the vehicle108 by the autonomous operation features or by the vehicle operator, anidentification module for identifying or verifying the identity of thevehicle operator, an information module for obtaining informationregarding a vehicle operator or vehicle 108, a use cost module fordetermining costs associated with operation of the vehicle 108, acomparison module for comparing one or more costs associated with owningor operating the vehicle 108, an update module for updating anautonomous operation feature of the vehicle 108, and/or other modules.

When implementing the exemplary autonomous vehicle operation method 300,the controller 204 of the on-board computer 114 may implement a vehiclecontrol module by the autonomous vehicle operation application 232 tocommunicate with the sensors 120 to receive information regarding thevehicle 108 and its environment and process that information forautonomous operation of the vehicle 108. In some embodiments, includingexternal source communication via the communication component 122 or thecommunication unit 220, the controller 204 may further implement acommunication module based upon the autonomous communication application234 to receive information for external sources, such as otherautonomous vehicles, smart infrastructure (e.g., electronicallycommunicating roadways, traffic signals, or parking structures), orother sources of relevant information (e.g., weather, traffic, localamenities). Some external sources of information may be connected to thecontroller 204 via the network 130, such as the server 140 orinternet-connected third-party databases (not shown). Although theautonomous vehicle operation application 232 and the autonomouscommunication application 234 are shown as two separate applications, itshould be understood that the functions of the autonomous operationfeatures may be combined or separated into any number of the softwareapplications 230 or the software routines 240.

In some embodiments, the controller 204 may further implement amonitoring module by the autonomous operation monitoring application 236to communicate with the server 140 to provide information regardingautonomous vehicle operation. This may include information regardingsettings or configurations of autonomous operation features, data fromthe sensors 120 regarding the vehicle environment, data from the sensors120 regarding the response of the vehicle 108 to its environment,communications sent or received using the communication component 122 orthe communication unit 220, operating status of the autonomous vehicleoperation application 232 and the autonomous communication application234, and/or commands sent from the on-board computer 114 to the controlcomponents (not shown) to operate the vehicle 108. The information maybe received and stored by the server 140 implementing the autonomousoperation information monitoring application 141, and the server 140 maythen determine the effectiveness of autonomous operation under variousconditions by implementing the feature evaluation application 142 andthe compatibility evaluation application 143. The effectiveness ofautonomous operation features and the extent of their use may be furtherused to determine risk associated with operation of the autonomousvehicle by the server 140 implementing a risk assessment module orinsurance module associated with the risk assessment application 144.

In addition to connections to the sensors 120, the mobile device 110 orthe on-board computer 114 may include additional sensors, such as theGPS unit 206 or the accelerometer 224, which may provide informationregarding the vehicle 108 for autonomous operation and other purposes.Furthermore, the communication unit 220 may communicate with otherautonomous vehicles, infrastructure, or other external sources ofinformation to transmit and receive information relating to autonomousvehicle operation. The communication unit 220 may communicate with theexternal sources via the network 130 or via any suitable wirelesscommunication protocol network, such as wireless telephony (e.g., GSM,CDMA, LTE, etc.), Wi-Fi (802.11 standards), WiMAX, Bluetooth, infraredor radio frequency communication, etc. Furthermore, the communicationunit 220 may provide input signals to the controller 204 via the I/Ocircuit 216. The communication unit 220 may also transmit sensor data,device status information, control signals, and/or other output from thecontroller 204 to one or more external sensors within the vehicle 108,mobile devices 110, on-board computers 114, and/or servers 140.

The mobile device 110 and/or the on-board computer 114 may include auser-input device (not shown) for receiving instructions or informationfrom the vehicle operator, such as settings relating to an autonomousoperation feature. The user-input device (not shown) may include a“soft” keyboard that is displayed on the display 202, an externalhardware keyboard communicating via a wired or a wireless connection(e.g., a Bluetooth keyboard), an external mouse, a microphone, or anyother suitable user-input device. The user-input device (not shown) mayalso include a microphone capable of receiving user voice input.

Exemplary Autonomous Vehicle Operation Method

FIG. 3 illustrates a flow diagram of an exemplary autonomous vehicleoperation method 300, which may be implemented by the autonomous vehicleinsurance system 100. The method 300 may begin at block 302 when thecontroller 204 receives a start signal. The start signal may be acommand from the vehicle operator through the user-input device toenable or engage one or more autonomous operation features of thevehicle 108. In some embodiments, the vehicle operator 108 may furtherspecify settings or configuration details for the autonomous operationfeatures. For fully autonomous vehicles, the settings may relate to oneor more destinations, route preferences, fuel efficiency preferences,speed preferences, and/or other configurable settings relating to theoperation of the vehicle 108. In some embodiments, fully autonomousvehicles may include additional features or settings permitting them tooperate without passengers or vehicle operators within the vehicle. Forexample, a fully autonomous vehicle may receive an instruction to find aparking space within the general vicinity, which the vehicle may dowithout the vehicle operator. The vehicle may then be returned to aselected location by a request from the vehicle operator via a mobiledevice 110 or otherwise. This feature may further be adapted to return afully autonomous vehicle if lost or stolen.

For other autonomous vehicles, the settings may include enabling ordisabling particular autonomous operation features, specifyingthresholds for autonomous operation, specifying warnings or otherinformation to be presented to the vehicle operator, specifyingautonomous communication types to send or receive, specifying conditionsunder which to enable or disable autonomous operation features, and/orspecifying other constraints on feature operation. For example, avehicle operator may set the maximum speed for an adaptive cruisecontrol feature with automatic lane centering. In some embodiments, thesettings may further include a specification of whether the vehicle 108should be operating as a fully or partially autonomous vehicle. Inembodiments where only one autonomous operation feature is enabled, thestart signal may consist of a request to perform a particular task(e.g., autonomous parking) and/or to enable a particular feature (e.g.,autonomous braking for collision avoidance). In other embodiments, thestart signal may be generated automatically by the controller 204 basedupon predetermined settings (e.g., when the vehicle 108 exceeds acertain speed and/or is operating in low-light conditions). In someembodiments, the controller 204 may generate a start signal whencommunication from an external source is received (e.g., when thevehicle 108 is on a smart highway or near another autonomous vehicle).

After receiving the start signal at block 302, the controller 204 mayreceive sensor data from the sensors 120 during vehicle operation atblock 304. In some embodiments, the controller 204 may also receiveinformation from external sources through the communication component122 and/or the communication unit 220. The sensor data may be stored inthe RAM 212 for use by the autonomous vehicle operation application 232.In some embodiments, the sensor data may be recorded in the data storage228 and/or transmitted to the server 140 via the network 130. The sensordata may alternately either be received by the controller 204 as rawdata measurements from one of the sensors 120 and/or may be preprocessedby the sensor 120 prior to being received by the controller 204. Forexample, a tachometer reading may be received as raw data and/or may bepreprocessed to indicate vehicle movement or position. As anotherexample, a sensor 120 comprising a radar and/or LIDAR unit may include aprocessor to preprocess the measured signals and send data representingdetected objects in 3-dimensional space to the controller 204.

The autonomous vehicle operation application 232, other applications230, and/or routines 240 may cause the controller 204 to process thereceived sensor data at block 306 in accordance with the autonomousoperation features. The controller 204 may process the sensor data todetermine whether an autonomous control action is required and/or todetermine adjustments to the controls of the vehicle 108. For example,the controller 204 may receive sensor data indicating a decreasingdistance to a nearby object in the vehicle's path and process thereceived sensor data to determine whether to begin braking (and, if so,how abruptly to slow the vehicle 108). As another example, thecontroller 204 may process the sensor data to determine whether thevehicle 108 is remaining with its intended path (e.g., within lanes on aroadway). If the vehicle 108 is beginning to drift or slide (e.g., as onice or water), the controller 204 may determine appropriate adjustmentsto the controls of the vehicle to maintain the desired bearing. If thevehicle 108 is moving within the desired path, the controller 204 maynonetheless determine whether adjustments are required to continuefollowing the desired route (e.g., following a winding road). Under someconditions, the controller 204 may determine to maintain the controlsbased upon the sensor data (e.g., when holding a steady speed on astraight road).

When the controller 204 determines an autonomous control action isrequired at block 308, the controller 204 may cause the controlcomponents of the vehicle 108 to adjust the operating controls of thevehicle to achieve desired operation at block 310. For example, thecontroller 204 may send a signal to open or close the throttle of thevehicle 108 to achieve a desired speed. Alternatively, the controller204 may control the steering of the vehicle 108 to adjust the directionof movement. In some embodiments, the vehicle 108 may transmit a messageor indication of a change in velocity or position using thecommunication component 122 and/or the communication unit 220, whichsignal may be used by other autonomous vehicles to adjust theircontrols. As discussed further below, the controller 204 may also log ortransmit the autonomous control actions to the server 140 via thenetwork 130 for analysis.

The controller 204 may continue to receive and process sensor data atblocks 304 and 306 until an end signal is received by the controller 204at block 312. The end signal may be automatically generated by thecontroller 204 upon the occurrence of certain criteria (e.g., thedestination is reached or environmental conditions require manualoperation of the vehicle 108 by the vehicle operator). Additionally, oralternatively, the vehicle operator may pause, terminate, and/or disablethe autonomous operation feature or features using the user-input deviceor by manually operating the vehicle's controls, such as by depressing apedal or turning a steering instrument. When the autonomous operationfeatures are disabled or terminated, the controller 204 may eithercontinue vehicle operation without the autonomous features or may shutoff the vehicle 108, depending upon the circumstances.

Where control of the vehicle 108 must be returned to the vehicleoperator, the controller 204 may alert the vehicle operator in advanceof returning to manual operation. The alert may include a visual, audio,and/or other indication to obtain the attention of the vehicle operator.In some embodiments, the controller 204 may further determine whetherthe vehicle operator is capable of resuming manual operation beforeterminating autonomous operation. If the vehicle operator is determinednot be capable of resuming operation, the controller 204 may cause thevehicle to stop and/or take other appropriate action.

Exemplary Monitoring Method During Operation

FIG. 4 illustrates a flow diagram depicting an exemplary monitoringmethod 400 during vehicle operation, which may be implemented by theautonomous vehicle insurance system 100. The method 400 may monitor theoperation of the vehicle 108 and adjust risk levels and rates based uponvehicle use. Although the exemplary embodiment is described as primarilyperformed by the on-board computer 114, the method 400 may beimplemented by the mobile device 110, the on-board computer 114, theserver 140, or a combination thereof. Upon receiving an indication ofvehicle operation at block 402, the on-board computer 114 may determinethe configuration and operating status of the autonomous operationfeatures (including the sensors 120 and the communication component 122)at block 404. The identity of the vehicle operator may be determinedand/or verified at block 406, which identity may be used to determine orreceive a vehicle operator profile at block 408. The vehicle operatorprofile may contain information regarding the vehicle operator's abilityto manually operate the vehicle and/or past use of autonomous operationfeatures by the vehicle operator. Information from the sensors 120and/or external data from the communication component 122 may be used atblock 410 to determine environmental conditions in which the vehicle 108is operating. Together, this information determined at blocks 404-410may be used at block 412 to determine one or more risk levels associatedwith operation of the vehicle, from which may be determined a costsassociated with an insurance policy at block 414. In some embodiments,information regarding the determined cost may be presented to thevehicle operator or other insurance customer associated with the vehicle108 at block 416. In still further embodiments, the vehicle operatorand/or insurance customer may be presented with recommendations oroptions regarding the cost associated with the insurance policy at block418. Presentation of options may assist the vehicle operator and/orinsurance customer in reducing the cost by allowing the vehicle operatorand/or insurance customer to select a lower-cost option (e.g., byadjusting the settings associated with the autonomous operationfeatures). In some embodiments, the vehicle operator and/or insurancecustomer may be able to select one or more of the options to effect anadjustment in the risk levels and/or insurance cost.

The method 400 may continue monitoring operation of the vehicle 108 atblock 420, and adjustments may be made to the risk levels and insurancecosts. If the settings associated with the autonomous operation featuresare determined to have changed at block 422 (e.g., as a result of thevehicle operator taking manual operation of additional controls), theone or more risk levels may be determined based upon the new settings atblock 412, in which case the blocks 414-422 may be repeated. When nochanges have been made to the settings, the method 400 may further checkfor changes to the environmental conditions and/or operating status ofthe autonomous operation features at block 424. If changes aredetermined to have occurred at block 424, the one or more risk levelsmay be determined based upon the new settings at block 412, as at block422. When no changes have occurred, the method 400 may determine whethervehicle operations are ongoing or whether operation is complete at block426. When vehicle operation is ongoing, the method 400 may continue tomonitor vehicle operation at block 420. When vehicle operation iscomplete, information regarding operation of the vehicle may be recordedat block 428, at which point the method 400 may terminate.

At block 402, the on-board computer 114 may receive an indication ofvehicle operation. This indication may be received from the vehicleoperator (either directly or through the mobile device 110), and/or itmay be generated automatically. For example, the on-board computer 114or the mobile device 110 may automatically generate an indication ofvehicle operation when the vehicle starts operation (e.g., upon engineignition, system power-up, movement of the vehicle 108, etc.). Uponreceiving the indication of vehicle operation, the on-board computer 114may initiate a system check and/or begin recording information regardingoperation of the vehicle 108.

At block 404, the on-board computer 114 may determine the configurationand operating status of one or more autonomous operation features of thevehicle 108. This may include determining the configuration, settings,and/or operating status of one or more hardware or software modules forcontrolling part or all of the vehicle operation, aftermarket componentsdisposed within the vehicle to provide information regarding vehicleoperation, and/or sensors 120 disposed within the vehicle. In someembodiments, a software version, model version, and/or otheridentification of the feature or sensor may be determined. In furtherembodiments, the autonomous operation feature may be tested to assessproper functioning, which may be accomplished using a test routine orother means. Additionally, the sensors 120 or the communicationcomponent 122 may be assessed to determine their operating status (e.g.,quality of communication connections, signal quality, noise,responsiveness, accuracy, etc.). In some embodiments, test signals maybe sent to one or more of the sensors 120, responses to which may bereceived and/or assessed by the on-board computer to determine operatingstatus. In further embodiments, signals received from a plurality ofsensors may be compared to determine whether any of the sensors aremalfunctioning. Additionally, signals received from the sensors may beused, in some embodiments, to calibrate the sensors.

At block 406, the on-board computer 114 may determine the identity ofthe vehicle operator. To determine the identity of the vehicle operator,the on-board computer 114 may receive and process information regardingthe vehicle operator. In some embodiments, the received information mayinclude sensor data from one or more sensors 120 configured to monitorthe interior of the vehicle. For example, a camera or other photographicsensor may provide photographic information regarding the vehicleoperator, which may be processed and compared with other photographicdata for a plurality of persons to determine the identity of the vehicleoperator. In further embodiments, the on-board computer may receiveinformation from a mobile computing device associated with the vehicleoperator, such as a mobile phone or wearable computing device. Forexample, a mobile phone may connect to the on-board computer 114, whichmay identify the vehicle operator. Additional steps may be taken toverify the identity of the vehicle operator, such as comparing a weightsensed on a seat or use of voice recognition algorithms.

At block 408, the on-board computer 114 may determine and/or access avehicle operator profile based upon the identity of the vehicle operatordetermined at block 406. The vehicle operator profile may includeinformation regarding the vehicle operator's style of operating thevehicle, including information regarding past operation of one or morevehicles by the vehicle operator. This information may further containpast vehicle operator selections of settings for one or more autonomousoperation features. In some embodiments, the on-board computer 114 mayrequest or access the vehicle operator profiled based upon thedetermined identity. In other embodiments, the on-board computer 114 maygenerate the vehicle operator profile from information associated withthe identified vehicle operator. The vehicle operator profile mayinclude information relating to one or more risks associated withoperation of the vehicle by the vehicle operator. For example, thevehicle operator profile for a driver may include information relatingto risk levels based upon past driving patters or habits in a variety ofrelevant environments, which may include risk levels associated withmanual operation of the vehicle by the driver. In some embodiments, thevehicle operator profile may include information regarding defaultsettings used by the vehicle operator for the autonomous operationfeatures.

At block 410, the on-board computer 114 may determine environmentalconditions within which the vehicle 108 is or is likely to be operating.Such environmental conditions may include weather, traffic, roadconditions, time of day, location of operation, type of road, and/orother information relevant to operation of the vehicle. Theenvironmental conditions may be determined based upon signals receivedfrom the sensors 120, from external data received through thecommunication component 122, and/or from a combination of sources. Theenvironmental conditions may then be used in determining risk levelsassociated with operation of the vehicle 108.

At block 412, the on-board computer may determine one or more risklevels associated with operation of the vehicle 108. The risk levels maybe determined based upon a combination of risk factors relating to theautonomous operation features and/or risk factors relating to thevehicle operation. Risks associated with the autonomous operationfeatures may be determined based upon the configuration and/or operatingstatus of the autonomous operation features, the settings of theautonomous operation features, and the vehicle environment. Risksassociated with the vehicle operation may be determined based upon theautonomous operation features settings (i.e., the extent to which thevehicle operator will be controlling vehicle operations) and/or thevehicle operator profile. The combined risk may account for thelikelihood of the autonomous operation features and/or the vehicleoperator controlling vehicle operations with respect to relevantfunctions of the vehicle 108.

At block 414, the on-board computer 114 may determine a cost associatedwith an insurance policy based upon the one or more risks. In someembodiments, the server 140 may receive information regarding thevehicle operator and the autonomous operation features and/or maydetermine the cost associated with the insurance policy based upon therisks. The cost may be based upon risk levels associated with separateautonomous operation features, interaction between autonomous operationfeatures, the design and capabilities of the vehicle 108, the pastoperating history of the vehicle operator as included in the vehicleoperator profile, and/or other information regarding the probability ofan accident, collision, and/or other loss event involving the vehicle108. Each of the separate risks may depend upon the environmentalconditions, and the risks may be weighted based upon the likelihood ofeach situation. In some embodiments, a total risk may be determinedrelating to operation of the vehicle under foreseeable conditions withspecific settings and configurations of autonomous operation features bya specific vehicle operator. The total risk may be used to determine oneor more costs associated with the insurance policy, such as a premiumand/or discount.

In some embodiments, information regarding the cost associated with theinsurance policy may be presented to the vehicle operator or insurancecustomer at block 416. The information may be presented by a display,such as the display 202 of the on-board computer 114 or the mobiledevice 110. The information may be presented either for informationalpurposes or to receive acceptance of the vehicle operator or insurancecustomer. The insurance cost information may include an indication ofone or more of a premium, rate, rating, discount, reward, special offer,points level, program, refund, and/or other costs associated with one ormore insurance policies. Additionally, or alternatively, summaryinformation may be presented regarding insurance costs, including a risklevel (e.g., high risk, low risk, a risk/cost level on a spectrum,etc.). In some embodiments, presentation of insurance cost informationmay be suppressed or delayed (e.g., cost information may be presented insummary form on a periodic billing statement).

In further embodiments, options or recommendations regarding the costassociated with the insurance policy may be presented to the vehicleoperator or insurance customer at block 418. The options orrecommendations may likewise be presented by a display, such as thedisplay 202 of the on-board computer 114 and/or the mobile device 110.The options or recommendations may include information regarding costsassociated with other settings or configurations of the autonomousoperation features (e.g., enabling additional features, selecting anoperating mode with lower risks under the determined environmentalconditions, etc.). In some embodiments, the recommendations or optionsmay be presented for informational purposes only, requiring the vehicleoperator or insurance customer to make any adjustments separately (e.g.,through a settings module or other means of adjusting settings for theautonomous operation features). In other embodiments, the vehicleoperator or insurance customer may select one or more of the options,whereby adjustments to the configuration or settings of the autonomousoperation features may be caused to be implemented by the on-boardcomputer 114 or other controlling device. In some embodiments, theoptions or recommendations may include options or recommendations toupdate the software version of one or more autonomous operationfeatures, in which case information regarding a cost associated withupdating the features (if applicable) may be presented. Once theinformation and/or options or recommendations regarding insurance costshave been presented at blocks 416-418 (including, in some embodiments,while such presentation is occurring), the on-board computer 114 maymonitor operation of the vehicle 108.

At block 420, the on-board computer 114 may monitor operation of thevehicle 108, including autonomous operation feature control decisions,signals from the sensors 120, external data from the communicationcomponent 122, and/or control decisions of the vehicle operator.Monitoring vehicle operation may include monitoring data receiveddirectly from the features, sensors, and/or other components, as well assummary information regarding the condition, movement, and/orenvironment of the vehicle 108. The on-board computer 114 and/or mobiledevice 110 may cause the operating data to be stored or recorded, eitherlocally in the data storage 228 and/or via server 140 in the programmemory 160 and/or the database 146. Monitoring may continue untilvehicle operation is complete (e.g., the vehicle has reached itsdestination and shut down), including during any updates or adjustments.

At block 422, the on-board computer 114 may determine whether anychanges have been made to the settings or configuration of theautonomous operation features. If such changes or adjustments have beenmade, the on-board computer 114 may proceed to determine new risk levelsand insurance costs at blocks 412-414 and/or present the information tothe vehicle operator or insurance customer at blocks 416-418, asdiscussed above. In some embodiments, minor changes below a minimumchange threshold may be ignored when determining whether any changeshave been made. In further embodiments, the cumulate effect of aplurality of such minor changes below the minimum change threshold maybe considered as a change at block 422 when the cumulative effect of theminor changes reaches and/or exceeds the minimum change threshold. Whenno changes to the settings or configuration of the autonomous operationfeatures are determined to have been made at block 422, the on-boardcomputer 114 may further determine whether any changes in theenvironmental conditions and/or operating status of the autonomousoperation features or sensors have occurred. Although these steps areillustrated separately for clarity, it should be understood that theymay be further divided or combined in various embodiments.

At block 424, the on-board computer 114 may determine whether anychanges have occurred to the environmental conditions of the vehicle 108and/or the operating status of the autonomous operation features,sensors 120, or communication component 122. Such changes may occur whenweather or traffic conditions change, when sensors 120 malfunction orbecome blocked by debris, and/or when the vehicle 108 leaves an areawhere external data is available via the communication component 122.When such changes occur, the risk levels associated with control of thevehicle 108 by the vehicle operator and the autonomous operationfeatures may likewise change. Therefore, it may be advantageous toadjust the use of the autonomous operation features to account for suchchanges. Thus, the on-board computer 114 may proceed to determine newrisk levels and insurance costs at blocks 412-414 and/or present theinformation to the vehicle operator or insurance customer at blocks416-418, as discussed above, when such changes are determined to haveoccurred at block 424. Similar to the determination at block 422, minorchanges below a minimum change threshold may be ignored at block 424,unless the cumulative effect of the changes reaches or exceeds theminimum change threshold. When no changes are determined to haveoccurred at block 424, the method 400 may continue to monitor theoperation of the vehicle 108 until vehicle operation is determined tohave ended.

At block 426, the on-board computer 114 may determine whether vehicleoperations are complete. This may include determining whether a commandto shut down the vehicle 108 has been received, whether the vehicle 108has remained idle at a destination for a predetermined period of time,and/or whether the vehicle operator has exited the vehicle 108. Untiloperation is determined at block 426 to be complete (i.e., when thevehicle trip has concluded), the on-board computer 114 may continue tomonitor vehicle operation at block 420, as discussed above. Whenoperation is determined to be complete at block 426, the on-boardcomputer 114 may further cause a record of the operation of the vehicle108 to be made or stored. Such records may include operating data (infull or summary form) and may be used for assessing risks associatedwith one or more autonomous operation features or the vehicle operator.As noted above, in some embodiments, records of operating data may begenerated and stored continually during operation. In some embodiments,the partial or completed records may be transmitted to the server 140 tobe stored in the database 146. After completion and recordation of thevehicle operation, the method 400 may terminate.

Exemplary Methods for Determining Operating Status

FIG. 5 illustrates a flow diagram depicting an exemplary operatingstatus assessment method 500 that may be used to determine operationstatus of the autonomous operation features, sensors 120, and/orcommunication component 122, as indicated in blocks 404 and 424 above.The method 500 may evaluate the autonomous operation features of thevehicle 108 (including sensors 120) and determine whether they areoperating correctly, are malfunctioning, and/or are operating withimpaired or degraded quality. Such determinations may be particularlyimportant as the vehicle 108 ages or in environments that may block ordamage sensors 120. In such cases, the original effectiveness of theautonomous operation features may be reduced as sensors become lessaccurate or processing of the sensor data is slowed (such as by softwareversion updates that improve accuracy but require greater computationalresources). The exemplary method 500 may be implemented regularly toensure appropriate risk assessment, as well as periodically to certifythe operating status level of the vehicle for roadworthiness orinsurance rate adjustment. In some embodiments, periodic evaluation maybe performed using special purpose computing devices and/or by licensedor authorized third parties. Periodic evaluation may further includemore thorough testing and analysis of the vehicle 108, which may includetesting at a test environment. Although the exemplary embodiment isdescribed as primarily performed by the on-board computer 114, themethod 500 may be implemented by the mobile device 110, the on-boardcomputer 114, the server 140, or a combination thereof.

Upon receiving a request to determine the operating status of theautonomous operation features of the vehicle 108 at block 502, theconfiguration of the sensors 120 may be determined at block 504. Thefunctioning of autonomous operation feature software routines mayfurther be determined at block 506. A test signal may be transmitted tothe sensors 120 at block 508, and/or sensor data may be received atblock 510. The sensor data may include a response to the test signal, aswell as other signals from the sensors based upon the vehicleenvironment or operation of the vehicle 108. Based upon the receivedinformation, the operating status of the autonomous operation featuresand components may be determined at block 512. If any impairments aredetected at block 514, the method 500 may attempt to remediate theimpairments at block 516. If impairments are detected to remain at block518 after the remediation attempt, an alert may be generated andpresented to the vehicle operator or an insurance customer at block 520.When no impairments are detected or after presentation of the alert, areport indicating the operational status of the autonomous operationfeatures may be generated at block 522. In some embodiments, the reportmay be transmitted to an insurer at block 524, and/or a cost associatedwith an insurance policy associated with the vehicle 108 may bedetermined at block 526. The determined cost may be presented with thereport at block 528 to the vehicle operator or insurance customer. Oncethe report has been presented, the exemplary method may end.

FIG. 6 illustrates a flow diagram of an exemplary operating statusmonitoring method 600 that may be used to determine operation status ofthe autonomous operation features, sensors 120, and/or communicationcomponent 122, in addition to or alternatively to the exemplary method500 above. The method 600 may be implemented while the vehicle 108 is inoperation to monitor the operating status of the autonomous operationfeatures and components. The method 600 may monitor the vehicleoperating data at block 602 to determine operating status of theautonomous operation features and components at block 604. When a changein operating status is detected at block 606, one or more correspondingchanges in risk levels may be determined at block 608. If the changes inrisk levels are determined to cause the risk levels to exceed an alertthreshold but not a critical threshold at blocks 610 and 612,respectively, an alert is generated and presented to the vehicleoperator at block 614. If the risk levels are determined to exceed thecritical threshold at block 612, the method 600 may determine whethercontrol of the vehicle 108 can be safely transferred to the vehicleoperator at block 616. If the vehicle operator is prepared and able toassume control of the vehicle 108, then vehicle operation may betransferred to the vehicle operator at block 620. If control cannot besafely transferred, the vehicle 108 may cease operations and shut downat block 618. Once the vehicle 108 is no longer operating, the method600 may terminate. Although the exemplary embodiment is described asprimarily performed by the on-board computer 114, the method 600 may beimplemented by the mobile device 110, the on-board computer 114, theserver 140, or a combination thereof.

Exemplary Methods for Control Hand-Off

FIGS. 7A-B illustrate flow diagrams depicting exemplary vehicleoperation hand-off methods 700 that may be used to transfer operation ofthe vehicle 108 from one or more autonomous operation features to thevehicle operator. FIG. 7A illustrates hand-off of control whendetermined necessary based upon heightened risk levels associated withoperation by the one or more autonomous operation features under theenvironmental conditions. FIG. 7B illustrates hand-off of control whenrequested by the vehicle operator while one or more autonomous operationfeatures are performing vehicle control tasks. The methods 700illustrated in FIGS. 7A and 7B may be combined or separately implementedin various embodiments. Although the exemplary embodiment is describedas primarily performed by the on-board computer 114, the exemplarymethod 700 may be implemented by the mobile device 110, the on-boardcomputer 114, the server 140, and/or a combination thereof.

Exemplary vehicle operation hand-off method 700 may be implemented atany time when one or more autonomous operation features are controllingpart or all of the operation of the vehicle 108. The method 700 maybegin by identifying the vehicle operator at block 702 and receiving avehicle operator profile for the vehicle operator at block 704. At block706, the operating data (including, in some embodiments, sensor data andexternal data) may be received and used to monitor operation of thevehicle 108. In some embodiments, a request to disable one or moreautonomous operation features may be received from the vehicle operatorat block 732. Autonomous risk levels associated with operation of thevehicle 108 by the autonomous operation features and operator risklevels associated with operation of the vehicle 108 by the vehicleoperator may be determined at block 708 and 710, respectively. Thedetermined risk levels may be used at block 712 to determine whether todisable one or more autonomous operation features. In some embodiments,the determination of whether to disable one or more autonomous operationfeatures may further be based upon the preparedness level of the vehicleoperator determined at block 716.

When it is determined to disable one or more autonomous operationfeatures at block 714, the method 700 may transfer control to thevehicle operator. In some embodiments, this may include determiningwhether the vehicle operator is able to safely assume control bydetermining whether the vehicle operator's preparedness level is above atransfer threshold level at block 718. If so, an alert may be presentedto the vehicle operator at block 720 to notify the vehicle operator ofthe transfer of control from the one or more autonomous operationfeatures before transferring operation at block 722. If the vehicleoperator's preparedness level is determined to be below the transferthreshold but above a minimum threshold at block 724, an alert may bepresented at block 730 to attempt to prepare the vehicle operator toassume control if the risk levels associated with continued operation bythe autonomous operation features do not exceed a critical riskthreshold at block 726. Once the alert is presented to the vehicleoperator at block 730, the vehicle operator's preparedness level may bedetermined again at block 716 and evaluated at block 718. If the risklevels exceed the critical threshold at block 726 or the vehicleoperator's preparedness level is below the minimum threshold at block724, the vehicle 108 may discontinue operation at block 728 and themethod 700 may end.

When it is determined not to disable the one or more autonomousoperation features at block 714, the method 700 may continue to monitorthe operating data at block 706. If the vehicle operator requested thatone or more autonomous operation features be disabled, the method 700may present an alert at block 734 to notify the vehicle operator thatdisabling the autonomous operation features is not recommended. In someembodiments, options to override the determination not to disable theautonomous operation features may be presented to the vehicle operatorat block 736, which the vehicle operator may select at block 738. If thevehicle operator is determined at block 740 to have not selected anoption to override the determination, the method 700 may continue tomonitor operation data at block 706. If the vehicle operator isdetermined at block 740 to have selected an option to override thedetermination, control of operation may be transferred from the one ormore autonomous operation features to the vehicle operator. In someembodiments, one or more risk levels associated with disabling theautonomous operation features may be determined at block 742. If therisk levels are determined to be below a critical threshold at block744, control may be transferred to the vehicle operator. If the risklevels meet or exceed the critical threshold at block 744, the vehicle108 may instead discontinue operation at block 728 and the method 700may end.

The method 700 as illustrated in FIG. 7A may begin at block 702 bydetermining the vehicle operator identity. The on-board computer 114 maydetermine the identity of the vehicle operator based upon informationfrom one or more sensors 120 within the vehicle 108 and/or an indicationof the vehicle operator identity from the mobile device 110 and/oranother device carried or worn by the vehicle operator, as discussedfurther below. Once the identity of the vehicle operator is determined,the on-board computer 114 may request, access, and/or receive a vehicleoperator profile associated with the vehicle operator at block 704,which may include information regarding risk levels associated withmanual vehicle operation by the vehicle operator under variousconditions, as discussed elsewhere herein. Such profile may, forexample, include details of past behavior of the vehicle operator underparticular conditions, such as weather conditions, traffic conditions,time of day, time spent continuously operating the vehicle, health,distraction levels, etc.

At block 706, the on-board computer 114 may receive operating data forthe vehicle 108 and/or monitor vehicle operation by one or moreautonomous operation features and/or the vehicle operator. In someembodiments, the on-board computer 114 may receive operating datarelating to the operation of the autonomous operation features, such assettings, configurations, software versions, control decisions, and/orother information indicating the actual or potential operation of thevehicle 108 by one or more autonomous operation features. The operatingdata may further include information from one or more sensors 120communicatively connected to the on-board computer 114, which mayinclude direct sensor signals generated by the sensors and/or processedor summarized sensor data based upon the direct sensor signals. In someembodiments, the operating data may further include external data fromthe communication component 122.

At block 708, the on-board computer 114 may determine one or moreautonomous operation risk levels associated with operation of thevehicle 108 by one or more autonomous operation features based upon theoperating data. The autonomous operation risk levels may further bebased upon risk levels determined for the same or similar autonomousoperation features, which risk levels may be determined by testingand/or actual loss data from other vehicles having the same or similarautonomous operation features. In some embodiments, informationregarding risks associated with the one or more autonomous operationfeatures may be obtained from the server 140 via the network 130. Infurther embodiments, the on-board computer 114 may transmit informationregarding the operating data to the server 140 and/or receive one ormore autonomous operation risk levels determined by the server 140.Additionally, or alternatively, the on-board computer 114 may transmitoperating data or information regarding the autonomous operation risklevels to the server 140 to determine and/or adjust one or more costsassociated with an insurance policy.

At block 710, the on-board computer 114 may determine one or moreoperator risk levels associated with operation of the vehicle 108 by thevehicle operator. Such operator risk levels may specifically correspondto the conditions of the vehicle, the vehicle's environment, or thevehicle operator. For example, such operator risk levels may indicate arisk assessment of the vehicle being driven manually by the vehicleoperator at night, in heavy traffic, with an underinflated tire, or whenthe vehicle operator is showing indications of drowsiness. Thisinformation regarding the vehicle operator's risk levels may be used todetermine whether the vehicle operator or the autonomous operationfeatures are best suited to safely operate the vehicle based uponcurrent conditions, as described below. In some embodiments, theoperator risk levels may be based upon operating data recorded while thevehicle 108 or another vehicle was previously controlled in whole orpart by the vehicle operator, and such data may be stored in a vehicleoperator profile, as discussed elsewhere herein. Additionally, oralternatively, traditional actuarial risk factors may be included indetermining the operator risk levels (e.g., age, vehicle, pastaccidents, etc.). This may be particularly useful, for example, wheredetailed operating data is not available for the vehicle operator.Similarly, operating data from a plurality of other vehicle operatorsmay be used to predict or estimate vehicle operator risk levels.

Regardless of how the operator risk levels are generated, such operatorrisk levels may be generated in advance of vehicle operation and storeduntil needed. For example, a risk profile or risk table may be generatedfor the vehicle operator periodically (e.g., weekly or monthly) andstored in the data storage 228 of the mobile device 110 or on-boardcomputer 114 for later use. In such embodiments, determining the one ormore operator risk levels may include accessing the stored profile ortable to obtain the risk levels during vehicle operation. As above,information regarding the vehicle operator and/or the operator risklevels may be received from, determined by, and/or transmitted to theserver 140. In some embodiments, the server 140 may further use theinformation for determining and/or adjusting one or more costsassociated with an insurance policy.

In one embodiment, the operator risk levels may be determined from acomparison of current road, environment, traffic, construction, orweather conditions with level settings indicating how the vehicleoperator typically drives in such conditions. Such actual driving ordriver behavior settings may be stored in the vehicle operator's vehicleoperator profile. The driving behavior settings may be associated withroad, weather, traffic, construction, or other traveling conditionsthrough which the vehicle is currently traveling, including urban orrural roads, and daylight versus night time driving. The drivingbehavior settings may be associated with autonomous or semi-autonomousvehicle features, including those discussed elsewhere herein. Furtherdriving behavior settings may be associated with the physical or mentalcondition of the vehicle operator, including alertness or emotionalstate.

At block 712, the on-board computer 114 may determine whether to disablethe operation of one or more autonomous operation features based uponthe determined autonomous operation risk levels and the determinedoperator risk levels. The determination may be based upon the one ormore autonomous operation risk levels applicable to operation of thevehicle 108 by the one or more autonomous operation features underenvironmental conditions in which the vehicle 108 is operating. Forexample, the on-board computer 114 may determine that an autonomousoperation feature (or combination of features) should be disabledbecause accuracy and/or reliability of the feature has dropped below anacceptable level for safe operation of the vehicle. Additionally, oralternatively, the determination may be based upon the relative risksassociated with operation of the vehicle 108 by the one or moreautonomous operation features and by the vehicle operator. For example,the on-board computer 114 may determine that the autonomous operationfeature (or combination of features) should be disabled when theassociated autonomous operation risk levels exceed the associatedoperator risk levels under the conditions of the vehicle environment. Asanother example, the on-board computer 114 may determine that theautonomous operation feature (or combination of features) should bedisabled based upon the autonomous operation risk levels, but mayfurther determine that the autonomous operation feature should not bedisabled (notwithstanding the autonomous operation risk levels) becausethe corresponding operator risk levels are greater than the autonomousoperation risk levels. Thus, the risk associated with autonomousoperation may be high, but the risk associated with manual operation bythe vehicle operator may be higher still. In such instances, theon-board computer 114 may determine whether the vehicle can be operatedwithin certain critical safety levels and/or whether stopping thevehicle 108 until risk levels are reduce may be feasible under theconditions (e.g., whether the vehicle can pull off of a road until heavyrain passes, etc.).

In some embodiments, the on-board computer 114 may only determine thatone or more autonomous operation features should be disabled if theautonomous operation risk levels exceed the corresponding operator risklevels by a minimum incremental amount and/or for a certain period oftime. In further embodiments, the determination at block 712 may bebased at least in part upon the availability and/or preparedness of thevehicle operator to assume control of relevant aspects of vehicleoperation from the one or more autonomous operation features. It shouldbe understood that the determination to disable the one or moreautonomous operation features may be made for all autonomous operationfeatures of the vehicle 108, for groups of autonomous operation featuresof the vehicle 108 (e.g., all autonomous operation features related tosteering the vehicle), and/or for individual autonomous operationfeatures of the vehicle 108.

When it is determined at block 714 that no autonomous operation featuresshould be disabled, the on-board computer 114 may continue to monitorthe operation of the vehicle 108 at block 706, as discussed above. Whenit is determined at block 714 that one or more autonomous operationfeatures should be disabled, however, the on-board computer 114 mayfurther determine a preparedness level of the vehicle operator at block716. The preparedness level may indicate the ability of the vehicleoperator to assume control of one or more functions of operating thevehicle 108 performed by the one or more autonomous operation featuresthat should be disabled. Preparedness levels may be based upon sensordata regarding the vehicle operator (e.g., data from operator-facingcameras, biometric sensors, or physiological sensors). For example,sensor data may determine that the vehicle operator may be asleep and/ordrowsy, resulting in a low preparedness level. In some embodiments, aplurality of preparedness levels may be determined, corresponding to aplurality of aspects of the vehicle operator's ability to make and/orexecute control decisions regarding the vehicle 108, includingalertness, distraction, irritation, fatigue, emotional state, and/orphysical health. The determined preparedness level of the vehicleoperator may then be used to determine whether and/or how to transferoperational control of the vehicle 108 to the vehicle operator.

At block 718, the on-board computer 114 may determine whether thevehicle operator's preparedness level is above a transfer thresholdwhere the vehicle operator may be able to safely assume controlfunctions from the one or more autonomous operation features. In someembodiments, the transfer threshold may be a predetermined value. Inother embodiments, the transfer threshold may be determined based uponthe operating status of the one or more autonomous operation features,the autonomous operation risk levels, the vehicle environment, and/orthe estimated time available to transfer control. When the preparednesslevel exceeds the transfer threshold, the on-board computer 114 maypresent an alert to the vehicle operator to warn the vehicle operator ofthe transfer of operation at block 720. This alert may notify thevehicle operator that the one or more autonomous operation features willbe disabled and provide time for the vehicle operator to assume controlof the operations. The alert may include auditory, visual, haptic,and/or other types of alerts to attract the vehicle operator'sattention, and information regarding the alert may be presented via thedisplay 202 or by other means. In some embodiments, the alert mayrequest or require a response from the vehicle operator to indicateattentiveness before transferring control. After presenting the alert tothe vehicle operator at block 720, the on-board computer 114 may disablethe one or more autonomous operation features, thereby transferringcontrol of the associated aspects of vehicle operation to the vehicleoperator at block 722.

In some embodiments, the on-board computer 114 may cause an indicationof the transfer of the control functions of the one or more autonomousoperation features to the vehicle operator to be generated and/ortransmitted to the server 140. The indication may further includeinformation regarding the one or more operator risk levels, operationdata, and/or other information relevant to risk determination and/orinsurance pricing. Transmission may occur via the network 130, either atthe time of the transfer or at a later time. The server 140 maydetermine and/or adjust a cost associated with an insurance policy basedupon the indication of the transfer of control, in any manner discussedherein.

When the preparedness level is determined to be at or below the transferthreshold at block 718, in some embodiments, the on-board computer 114may further determine whether the preparedness level is above a minimumthreshold at block 724. The minimum threshold may be set to a levelindicating the vehicle operator may be prepared to assume operation ofthe vehicle functions within a sufficiently short period of time, whichmay be predetermined or determined based upon the circumstances of thehand-off in a manner similar to that discussed above. For example, theminimum threshold may indicate a level where the vehicle operator isawake. If the vehicle operator's preparedness level is above the minimumthreshold at block 724, the on-board computer 114 may attempt to alertthe vehicle operator that control should be transferred and/or one ormore autonomous operation features should be disabled at blocks 726-730.

If the vehicle operator's preparedness level is below the minimumthreshold, the on-board computer 114 may cause the vehicle 108 todiscontinue operation and/or shut down at block 728. In order to safelydiscontinue operation of the vehicle 108, the on-board computer 114 maycause the vehicle 108 to navigate to a location where it can safely stopand/or shut down (e.g., a parking lot or road shoulder). In someembodiments, the determination of a location to discontinue operationsmay be based in part upon the one or more autonomous operation risklevels associated with continuing operation of the vehicle 108 by theautonomous operation features.

In some embodiments, the on-board computer 114 may determine whether theone or more autonomous operation risk levels exceed a critical riskthreshold at block 726. The critical risk level may be predetermined ordetermined based upon the operating data, indicating a risk level abovewhich the vehicle 108 should immediately begin stopping anddiscontinuing operations. For example, the total failure of a LIDARsystem of the vehicle 108 may require immediate reversion to manualoperation or cessation of vehicle operation. If the one or moreautonomous operation risks are above the critical risk threshold (eitherindividually or cumulatively), the vehicle 108 may discontinue operationat block 728, as discussed above. If the one or more autonomousoperation risks do not exceed the critical risk threshold, however, theon-board computer 114 may cause an alert to be presented to the vehicleoperator at block 730 to attempt to increase the vehicle operator'spreparedness level. In addition to attempting to attract the vehicleoperator's attention, the alert may indicate that the one or moreautonomous operation features should be disabled. In some embodiments,presentation of the alert may include adjusting the vehicle operator'senvironment (e.g., interrupting music playback, adjusting temperature,and/or varying fan speed). Following presentation of the alert at block730, the on-board computer 114 may continue to monitor and/or assess thevehicle operator to determine a new preparedness level at block 716. Theblocks 716-730 may be implemented repeatedly until either a transfer ofcontrol to the vehicle operator occurs at block 722 or vehicle operationis discontinued at block 728.

The method 700 as illustrated in FIG. 7B may likewise be implemented bythe on-board computer 114 to handle transfers of control from one ormore autonomous operation features to the vehicle operator. At blocks702 and 704, the on-board computer 114 may determine the vehicleoperator's identity and receive an associated vehicle operator profile,as discussed above. At block 706, the on-board computer 114 may proceedto receive and/or monitor operating data, as discussed above. At block732, the on-board computer 114 may receive from the vehicle operatorand/or a third party a request to disable one or more autonomousoperation features. The request may indicate specific autonomousoperation features or groups of autonomous operation features todisable, and/or the request may include a request to implement a mode orprofile including adjusting settings for one or more autonomousoperation features. At blocks 708 and 710, the on-board computer 114 maydetermine one or more autonomous operation risk levels and one or moreoperator risk levels, as discussed above. Similarly, the on-boardcomputer 114 may determine a preparedness level of the vehicle operatorat block 716, as discussed above.

At block 712, the on-board computer 114 may determine whether to disablethe one or more autonomous operation features based upon the autonomousoperation risk levels, the operator risk levels, and/or the preparednesslevel. As discussed above, the determination may be based upon theabsolute and/or relative risks associated with operation by the one ormore autonomous operation features and/or the vehicle operator. In someembodiments, determining whether to disable the one or more autonomousoperation features may include determining whether the absolute and/orrelative risk level associated with operation of the vehicle by thevehicle operator without the autonomous operation features is within anacceptable range of risk levels. In some embodiments, the on-boardcomputer 114 may determine not to disable autonomous operation featuresif the operator risk levels associated with manual control of thevehicle 108 may lead to a sharp increase in risk above a criticalthreshold under the environmental conditions in which the vehicle isoperating. For example, a vehicle operator unaccustomed to driving insnow may request to disable autonomous operation features on asnow-covered road, in which case the on-board computer 114 may determinenot to disable the autonomous operation features if the operator risklevels are too high. In further embodiments, the one or more operatorrisk levels may be adjusted based upon the vehicle operator'spreparedness level. In other embodiments, the vehicle operator'spreparedness level may be used to determine whether to disable the oneor more autonomous operation features, as discussed with respect to FIG.7A.

When it is determined that the one or more autonomous operation featuresmay be disabled at block 714, the on-board computer 114 may cause analert to be presented to the vehicle operator at block 720 in advance oftransferring control at block 722, as discussed above. When it isdetermined not to disable the one or more autonomous operation featuresat block 714, the on-board computer 114 may cause another alert to bepresented to the vehicle operator at block 734, indicating thedetermination not to disable the one or more autonomous operationfeatures. In some embodiments, the alert at block 734 may indicate thereasons for not disabling the one or more autonomous operation features,the strength of the recommendation against disabling the one or moreautonomous operation features, an indication of a change in risk levelsassociated with disabling the one or more autonomous operation features,an adjustment to a cost associated with an insurance policy related todisabling the one or more autonomous operation features, and/or otherrelevant information regarding disabling the one or more autonomousoperation features.

At block 736, in some embodiments, the on-board computer 114 may furthercause an option to override the determination not to disable the one ormore autonomous operation features to be presented to the vehicleoperator. In some embodiments, multiple options may be presented toallow the vehicle operator to override the determination with respect tosome or all of the autonomous operation features. When the vehicleoperator selects the option to override the determination, the on-boardcomputer 114 may receive an indication of the selection at block 738. Atblock 740, the on-board computer 114 may determine whether an indicationof a selection of an option to override the determination has beenreceived. If no such indication has been received, the one or moreautonomous operation features may continue to operate, and the on-boardcomputer 114 may continue to monitor the operating data at block 706.

If an indication of a selection by the vehicle operator of an option tooverride the determination is received, the on-board computer 114 maystill, in some embodiments, determine whether the risk from disablingthe one or more autonomous operation features is within an acceptablerange. At block 742, the on-board computer may determine one or morerisk levels associated with disabling the one or more autonomousoperation features based upon one or more of the operation data, theoperator risk levels, and/or the autonomous operation risk levels. Forexample, the risk level associated with overriding a determination notto disable anti-lock brakes on an icy road may lead to a significantincrease in the risk level associated with hard braking, as well as ahigh risk level for sliding or loss of steering control, particularlyfor a vehicle operator unfamiliar with such driving conditions. At block744, the on-board computer 114 may determine whether the one or morerisk levels are below a critical threshold. The critical threshold mayrepresent a minimum standard of safe operation of the vehicle 108. Insome embodiments, the on-board computer 114 may cause the one or moreautonomous operation features to be disabled only if the one or morerisk levels associated with disabling the one or more autonomousoperation features are below the critical threshold. If the one or morerisk levels are below the critical threshold, the vehicle 108 maydiscontinue operations at block 728, as discussed above. If the one ormore risk levels meet or exceed the critical threshold, the on-boardcomputer 114 may present an alert at block 720 and transfer control tothe vehicle operator by disabling the one or more autonomous operationfeatures at block 722, as above. In some embodiments, the on-boardcomputer 114 may further transmit an indication that the one or moreautonomous operation features have been disabled to the server 140,which may determine and/or adjust a cost associated with an insurancepolicy based upon a change in risk levels, as discussed elsewhereherein.

According to certain aspects, a computer-implemented method foroperating an autonomous or semi-autonomous vehicle may be provided. Withthe customer's permission, an identity of a vehicle operator may beidentified and a vehicle operator profile may be retrieved. Operatingdata regarding autonomous operation features operating the vehicle maybe received from vehicle-mounted sensors. When a request to disable anautonomous feature is received, a risk level for the autonomous featureis determined and compared with a driver behavior setting for theautonomous feature stored in the vehicle operator profile. Based uponthe risk level comparison, the autonomous vehicle retains control ofvehicle or the autonomous feature is disengaged depending on which isthe safer driver—the autonomous vehicle or the vehicle human occupant.As a result, unsafe disengagement of self-driving functionality forautonomous vehicles may be alleviated. Insurance discounts may beprovided for autonomous vehicles having this safety functionality.

With all of the foregoing, a customer may opt into a rewards or othertype of program, and willingly share their vehicle data with aninsurance provider. In return, risk averse drivers and vehicle ownersmay receive discounts or insurance cost savings related to auto andother types of insurance from the insurance provider.

Selecting Best “Driver”

A. Current Road Conditions

In one aspect, a computer-implemented method of enhancing vehicleoperation safety may be provided. The method may include (1)determining, via one or more processors (such as one or more local orremote processors, e.g., vehicle-mounted local processors or insuranceprovider remote processors), a current environment (or condition)through which a vehicle is traveling or about to travel through, thecurrent environment (or condition) being associated with, or including,weather, traffic, construction, and/or road conditions, the vehiclebeing equipped with autonomous or semi-autonomous functionality ortechnology; (2) determining, via the one or more processors, whether itis safer for a human to drive the vehicle or for the vehicle toautomatically drive itself (or otherwise engage the autonomous orsemi-autonomous functionality or technology) based upon, or given, thecurrent environment (or condition); and/or (3) generating, via the oneor more processors, (i) an indication or recommendation to a driver todrive the vehicle if it is determined that it is safer for an average ortypical human (or even that specific driver) to drive the vehicle giventhe current environment (or condition), or (ii) an indication orrecommendation to the driver to engage the autonomous or semi-autonomousfunctionality or technology if it is determined that it is safer for thevehicle to automatically drive itself (or otherwise engage theautonomous or semi-autonomous functionality or technology) given thecurrent environment (or condition) to facilitate safer vehicle traveland/or vehicle accident prevention. The method may include additional,fewer, or alternate actions, including those discussed elsewhere herein.

For instance, when it is determined that it is safer for the vehicle toautomatically drive itself given the current environment (or condition),the one or more processors may automatically engage the autonomous orsemi-autonomous functionality or technology. Additionally oralternatively, when it is determined that it is safer for an averagehuman (or the specific driver, e.g., based upon a driver profile for thespecific driver) to drive the vehicle given the current environment (orcondition), the one or more processors may prevent engagement of theautonomous or semi-autonomous functionality or technology.

The method may also include gathering or collecting, at or via the oneor more processors, driver behavior data of a specific driver over time,such as from one or more vehicle-mounted sensors that are in wired orwireless communication with the one or more processors; and/or buildingor updating a driver profile for the specific driver, at or via the oneor more processors, from the driver behavior data gathered or collectedover time. As a result, determining, via the one or more processors,whether it is safer for a human to drive the vehicle or for the vehicleto automatically drive itself based upon, or given, the currentenvironment (or condition) may take into consideration the driverprofile and/or driver behavior data associated with the specific driver.

The driver behavior data and/or driver profile may indicate how well thespecific driver drives in rain, snow, sleet, ice, heavy traffic, roadconstruction, stop-and-go traffic, bumper-to-bumper traffic, country orrural traffic, and/or city or downtown street traffic. The currentenvironment (or condition) may include or be rain, ice, snow, fog, heavytraffic, bumper-to-bumper traffic, road construction, city traffic,country or rural traffic, and/or may be associated with a type of road,such as a two-lane or four-lane highway, or downtown city street orother street having several traffic lights.

The method may include updating or adjusting an insurance policy,premium, rate, reward, rewards or points program, and/or discount basedupon the driver accepting or following the recommendation (regardingvehicle driver or mode of operation).

Determining, via one or more processors, a current environment (orcondition) through which a vehicle is traveling or about to travelthrough may include the one or more processors receiving current orupdated information regarding weather, traffic, construction, and/orroad conditions via a wired or wireless communication network, such asover the internet and/or from third party or government websites.Additionally or alternatively, determining, via one or more processors,a current environment (or condition) through which a vehicle istraveling or about to travel through may include the one or moreprocessors receiving current or updated information regarding weather,traffic, construction, and/or road conditions from one or morevehicle-mounted sensors or cameras. Further, determining, via one ormore processors, a current environment (or condition) through which avehicle is traveling or about to travel through may include the one ormore processors receiving current or updated information regardingweather, traffic, construction, and/or road conditions via wirelesscommunication, such as via wireless communication or data transmissionfrom another vehicle (vehicle-to-vehicle communication), from smartinfrastructure (infrastructure-to-vehicle communication) (e.g., fromsmart traffic lights, smart street signs, smart exit ramps, smartbridges, and/or smart tollbooths), and/or from mobile devices(pedestrian-to-vehicle communication).

The method may include adjusting or updating, at or via an insuranceprovider remote processor or server, a life, home, renters, and/orhealth insurance policy (or associated premium, rate, rewards or pointsprogram, and/or discount) based upon driver usage of autonomous orsemi-autonomous functionality or technology; an amount that the driveruses one or more different autonomous or semi-autonomous functionalitiesor technologies; and/or how well the specific driver uses, engages,and/or operates one or more autonomous or semi-autonomousfunctionalities or technologies.

B. Current Environment

In another aspect, a computer-implemented method of enhancing vehicleoperation safety may be provided. The method may include (a)determining, via one or more processors (such as one or more local orremote processors, e.g., vehicle-mounted local processors or insuranceprovider remote processors), a current environment (or condition)through which a vehicle is traveling or about to travel through, thecurrent environment (or condition) being associated with, or including,weather, traffic, construction, and/or road conditions, the vehiclebeing equipped with autonomous or semi-autonomous functionality ortechnology; (b) determining, via the one or more processors, that it isunsafe for the vehicle to operate with the autonomous or semi-autonomousfunctionality or technology engaged in, or given, the currentenvironment (or condition) through which the vehicle is traveling orabout to travel through; and/or (c) generating, via the one or moreprocessors, an indication or recommendation to a driver to (1) continueto personally drive the vehicle; (2) take over human control of thevehicle (if the vehicle is driving itself); (3) not engage theautonomous or semi-autonomous functionality or technology; and/or (4)disengage the autonomous or semi-autonomous functionality or technologywhen it is determined that it is unsafe for the vehicle to operate withthe autonomous or semi-autonomous functionality or technology engagedin, or given, the current environment (or condition) through which thevehicle is traveling or about to travel through to facilitate safevehicle travel and/or vehicle accident prevention. The method mayinclude additional, fewer, or alternate actions, including thosediscussed elsewhere herein.

For instance, the current environment (or condition) through which it isdetermined that it is unsafe for the vehicle to operate with theautonomous or semi-autonomous functionality or technology engaged may beor include rain, ice, snow, heavy traffic, bumper-to-bumper traffic,road construction, and/or may be associated with a certain type of road,such as a two-lane or four-lane highway, or downtown city street.

The method may include updating or adjusting an insurance policy,premium, rate, reward, rewards or point program, and/or discount basedupon the driver accepting or following the recommendation (regardingvehicle driver (such as either human or vehicle) or mode of operation),or a percentage of time that the driver follows the recommendationsprovided.

Determining, via one or more processors, a current environment (orcondition) through which a vehicle is traveling or about to travelthrough may include the one or more processors receiving current orupdated information regarding weather, traffic, construction, and/orroad conditions via a wired or wireless communication network, such asover the internet and/or from third party or government websites.Additionally or alternatively, determining, via one or more processors,a current environment (or condition) through which a vehicle istraveling or about to travel through may include the one or moreprocessors receiving current or updated information regarding weather,traffic, construction, and/or road conditions from one or morevehicle-mounted sensors, cameras, or communication networks that captureinformation regarding conditions external to, and/or in front of, thevehicle. Further, determining, via one or more processors, a currentenvironment (or condition) through which a vehicle is traveling or aboutto travel through may include the one or more processors receivingcurrent or updated information regarding weather, traffic, construction,and/or road conditions via wireless communication, such as via wirelesscommunication or data transmission from another vehicle(vehicle-to-vehicle communication), from smart infrastructure(infrastructure-to-vehicle communication) (e.g., from smart trafficlights, smart street signs, smart bridges or exit ramps, or smarttollbooths or overpasses), and/or from mobile devices(pedestrian-to-vehicle communication).

The method may include adjusting or updating, at or via an insuranceprovider remote processor or server, a life, home, renters, and/orhealth insurance policy (or associated premium, rate, rewards or pointsprogram, and/or discount) based upon driver usage of autonomous orsemi-autonomous functionality or technology; an amount that the driveruses one or more different autonomous or semi-autonomous functionalitiesor technologies; and/or how well the specific driver uses, engages,and/or operates one or more autonomous or semi-autonomousfunctionalities or technologies.

C. Safety Comparison & Recommendations

In another aspect, a computer-implemented method of enhancing vehicleoperation safety may be provided. The method may include (i)determining, via one or more processors (such as one or more local orremote processors, e.g., vehicle-mounted local processors or insuranceprovider remote processors), a current environment (or condition)through which a vehicle is traveling or about to travel through, thecurrent environment (or condition) being associated with, or including,weather, traffic, construction, and/or road conditions, the vehiclebeing equipped with autonomous or semi-autonomous functionality ortechnology; (ii) determining, via the one or more processors, whether itis safer for (1) a human driver to drive the vehicle, or (2) the vehicleto operate with the autonomous or semi-autonomous functionality ortechnology engaged based upon, or given, the current environment (orcondition) through which the vehicle is traveling or about to travelthrough; and/or (iii) generating, via the one or more processors, anindication or recommendation to the human driver whether it is safer for(a) the human driver to drive the vehicle, or (b) the vehicle to operatewith the autonomous or semi-autonomous functionality or technologyengaged based upon, or given, the current environment (or condition)through which the vehicle is traveling or about to travel through tofacilitate vehicle accident prevention and/or safer vehicle operation ortravel. The method may include additional, fewer, or alternate actions,including those discussed elsewhere herein.

For instance, determining, via the one or more processors, whether it issafer for (1) a human driver to drive the vehicle, or (2) the vehicle tooperate with the autonomous or semi-autonomous functionality ortechnology engaged based upon, or given, the current environment (orcondition) through which the vehicle is traveling or about to travelthrough may be based upon (such as based upon a comparison of): (a)driving behavior or characteristic data for typical human drivers, or adriving profile for a specific driver built over time; and/or (b) safetyratings, profiles, or characteristic data for the autonomous orsemi-autonomous functionality or technology.

The method may include updating or adjusting an insurance policy,premium, rate, reward, rewards or points program, and/or discount basedupon the driver accepting or following the recommendation (regardingvehicle driver (human or vehicle) or mode of operation), or a percentageof time that the driver follows recommendations provided. Determining,via one or more processors, a current environment (or condition) throughwhich a vehicle is traveling or about to travel through may include theone or more processors receiving current or updated informationregarding weather, traffic, construction, and/or road conditions via awired or wireless communication network, such as over the internetand/or from third party or government websites.

Determining, via one or more processors, a current environment (orcondition) through which a vehicle is traveling or about to travelthrough may include the one or more processors receiving current orupdated information regarding weather, traffic, construction, and/orroad conditions from one or more vehicle-mounted sensors, cameras and/orcommunication networks that capture information regarding conditionsexternal to, and/or in front of, the vehicle. Additionally oralternatively, determining, via one or more processors, a currentenvironment (or condition) through which a vehicle is traveling or aboutto travel through may include the one or more processors receivingcurrent or updated information regarding weather, traffic, construction,and/or road conditions via wireless communication, such as via wirelesscommunication or data transmission from another vehicle(vehicle-to-vehicle communication) (e.g., from another vehicle travelingahead of the vehicle or from a smart train); from smart infrastructure(infrastructure-to-vehicle communication) (e.g., from smart trafficlights, smart street signs, smart tollbooths, smart overpasses, smartbuildings, smart bridges, smart train or bus system); and/or from mobiledevices (pedestrian-to-vehicle communication).

The method may include adjusting or updating, at or via an insuranceprovider remote processor or server, a life, home, renters, or healthinsurance policy (or associated premium, rate, rewards or pointsprogram, and/or discount) based upon driver usage of autonomous orsemi-autonomous functionality or technology; an amount that the driveruses one or more different autonomous or semi-autonomous functionalitiesor technologies; and/or how well the specific driver uses, engages,and/or operates one or more autonomous or semi-autonomousfunctionalities or technologies.

D. Automatic Engagement

In another aspect, a computer-implemented method of enhancing vehicleoperation safety may be provided. The method may include automaticallyengaging, via one or more processors (such as one or more local orremote processors, e.g., vehicle-mounted local processors or insuranceprovider remote processors), an autonomous or semi-autonomousfunctionality or technology of a vehicle when it is determined, by theone or more processors, that it is safer for the vehicle to operate withthe autonomous or semi-autonomous functionality or technology engagedbased upon, and/or comparison of: (a) one or more current environmentalor road conditions through which the vehicle is currently traveling, orabout to travel through, that are automatically determined by the one ormore processors; (b) safety ratings, profiles, and/or characteristicdata for the autonomous or semi-autonomous functionality or technology;and/or (c) driving behavior data and/or a driver profile for a specificdriver that indicates how well the specific driver drives or otherwiseoperates the vehicle in the one or more current environmental or roadconditions. The method may include additional, fewer, or alternateactions, including those discussed elsewhere herein.

For instance, the one or more current environmental or road conditionsmay include one or more weather, traffic, construction, road, and/ortime of day conditions, and/or a weather condition indicates rain, snow,sun, clear, ice, cloudy, foggy, visibility, day (light outside), and/ornight (dark outside). The method may include updating or adjusting aninsurance policy, premium, rate, rewards or points program, and/ordiscount based upon the vehicle being configured to automatically engagethe autonomous or semi-autonomous functionality or technology.

The method may include adjusting or updating, at or via an insuranceprovider remote processor or server, a life, home, renters, and/orhealth insurance policy (or associated premium, rate, rewards or pointsprogram, and/or discount) based upon driver usage of autonomous orsemi-autonomous functionality or technology; an amount that the driveruses one or more different autonomous or semi-autonomous functionalitiesor technologies; and/or how well the specific driver uses, engages,and/or operates one or more autonomous or semi-autonomousfunctionalities or technologies.

E. Driving Behavior

In another aspect, a computer-implemented method of enhancing vehicleoperation safety may be provided. The method may include (1) gatheringor collecting, at or via one or more processors (such as one or morelocal or remote processors, e.g., vehicle-mounted local processors orinsurance provider remote processors), driving behavior and/orcharacteristic data of a specific driver while the specific driver isdriving a vehicle (or otherwise operating the vehicle) over time, thedriving behavior and/or characteristic data being associated with,scoring, or indicative of, how well the driver drives (or otherwiseoperates the vehicle) in certain conditions, the certain conditionsbeing associated with weather, traffic, construction, road, and/or otherenvironmental conditions; (2) building a driver profile for the specificdriver, via the one or more processors, from the driving behavior and/orcharacteristic data of the specific driver gathered or collected overtime; (3) identifying or receiving, via the one or more processors, acurrent condition, such as a current weather, traffic, construction,and/or road condition (through which the vehicle is traveling through,or about to travel through); (4) determining, via the one or moreprocessors, that a driving score or rating for the specific driver isbelow a certain threshold (such as a driving score or rating for anautonomous or semi-autonomous functionality or technology) based uponanalysis or comparison of (a) the current condition, and (b) the driverprofile, and/or the driving behavior and/or characteristic data of thespecific driver; and/or (5) in response, via the one or more processors,generating a message or recommendation for the driver to engage theautonomous or semi-autonomous functionality or technology of the vehicleand/or automatically engaging the autonomous or semi-autonomousfunctionality or technology to facilitate safer vehicle travel oraccident prevention in unfavorable driving conditions, such as badweather or road conditions. The method may include additional, fewer, oralternate actions, including those discussed elsewhere herein.

For instance, the method may further include, when it is determined, viathe one or more processors, that the driving score and/or rating for thespecific driver is below the certain threshold (such as the drivingscore or rating for an autonomous or semi-autonomous functionality ortechnology) given the current condition—which may indicate that theautonomous or semi-autonomous functionality or technology drives betterin the unfavorable condition than the specific driver—the one or moreprocessors may (i) prevent the specific driver from turning off theautonomous or semi-autonomous functionality or technology if previouslyengaged, or (ii) automatically engage the autonomous or semi-autonomousfunctionality or technology if not previously engaged to facilitatesafer vehicle travel and/or accident prevention in unfavorableconditions.

The method may include updating or adjusting, via the one or moreprocessors, an insurance policy, premium, rate, rewards or pointsprogram, and/or discount based upon the driver accepting or followingthe recommendation (regarding vehicle driver (such as either a human orvehicle driver being recommended) or mode of operation), or a percentageof time that the driver follows recommendations provided.

Identifying or receiving, via the one or more processors, the currentcondition through which a vehicle is traveling, or about to travelthrough, may include the one or more processors receiving current orupdated information regarding weather, traffic, construction, and/orroad conditions via a wired or wireless communication network, such asover the internet and/or from third party or government websites.Additionally or alternatively, identifying or receiving, via one or moreprocessors, the current condition through which a vehicle is traveling,or about to travel through, may include the one or more processorsreceiving current or updated information regarding weather, traffic,construction, and/or road conditions from one or more vehicle-mountedsensors, cameras, and/or communication networks that capture informationregarding conditions external to, and/or in front of, the vehicle. Also,identifying or receiving, via one or more processors, a currentcondition through which a vehicle is traveling, or about to travelthrough, may include the one or more processors receiving current orupdated information regarding weather, traffic, construction, and/orroad conditions via wireless communication, such as via wirelesscommunication or data transmission from another vehicle(vehicle-to-vehicle communication) (e.g., from another vehicle travelingahead of the vehicle); from smart infrastructure(infrastructure-to-vehicle communication) (e.g., from smart trafficlights, smart street signs, smart tollbooths, smart overpasses, smartbridges, or smart buildings); and/or from mobile devices(pedestrian-to-vehicle communication).

The method may include adjusting or updating, at or via an insuranceprovider remote processor or server, a life, home, renters, and/orhealth insurance policy (or associated premium, rate, rewards or pointsprogram, and/or discount) based upon driver usage of autonomous orsemi-autonomous functionality or technology; an amount that the driveruses one or more different autonomous or semi-autonomous functionalitiesor technologies; and/or how well the specific driver uses, engages,and/or operates one or more autonomous or semi-autonomousfunctionalities or technologies.

F. Driver Profile

In another aspect, a computer-implemented method of providing orenhancing vehicle operation safety may be provided. The method mayinclude (1) building a driver profile over time, via one or moreprocessors (such as one or more local or remote processors, e.g.,vehicle-mounted local processors or insurance provider remoteprocessors), the driving profile including driving behavior and/orcharacteristic data associated with a specific driver of a vehicle, thedriver behavior and/or characteristic data associated with drivingscores or ratings for different environmental or roads conditions, suchas different weather, traffic, construction, or road conditions; (2)identifying (or receiving data indicative of), via the one or moreprocessors, one or more current environmental or road conditions (orother unfavorable driving condition) through which a vehicle istraveling or approaching; and/or (3) determining, via the one or moreprocessors, that an autonomous or semi-autonomous functionality ortechnology drives the vehicle better than the specific driver in the oneor more current environmental or road conditions based upon analysis orcomparison of, via the one or more processors: (a) the currentenvironmental or road conditions (or other unfavorable drivingcondition); (b) the driving profile, and/or driving behavior and/orcharacteristic data associated with the specific driver; and/or (c)driving score or rating of the autonomous or semi-autonomousfunctionality or technology, such as a score or rating associated withindividual environmental or road conditions for that autonomous orsemi-autonomous functionality or technology. The method may alsoinclude, when it is determined that the autonomous or semi-autonomousfunctionality or technology drives (or operates) the vehicle better thanthe specific driver in the one or more current environmental or roadconditions, via the one or more processors: (i) preventing the specificdriver from turning off the autonomous or semi-autonomous functionalityor technology; (ii) automatically engaging the autonomous orsemi-autonomous functionality to facilitate safer driving; and/or (iii)recommending that the specific driver employ or engage the autonomous orsemi-autonomous functionality or technology to facilitate safer vehicleoperation or accident prevention. The method may include additional,fewer, or alternate actions, including those discussed elsewhere herein.

For instance, the method may include updating or adjusting an insurancepolicy, premium, rate, rewards or points program, and/or discount basedupon the driver accepting or following the recommendation (regardingvehicle driver or mode of operation), or a percentage of time that thedriver follows recommendations provided. Identifying (or receiving dataindicative of), via one or more processors, a current environmental orroad condition (or other unfavorable driving condition) through whichthe vehicle is traveling, or approaching, may include the one or moreprocessors receiving current or updated information regarding weather,traffic, construction, and/or road conditions via a wired or wirelesscommunication network, such as over the internet and/or from third partyor government websites.

Identifying (or receiving data indicative of), via one or moreprocessors, a current environmental or road condition (or otherunfavorable driving condition) through which the vehicle is traveling,or approaching, may include the one or more processors receiving currentor updated information regarding weather, traffic, construction, and/orroad conditions from one or more vehicle-mounted sensors or cameras thatcapture information regarding conditions external to, and/or in frontof, the vehicle. Additionally or alternatively, identifying (orreceiving data indicative of), via one or more processors, a currentenvironmental or road condition (or other unfavorable driving condition)through which the vehicle is traveling or approaching may include theone or more processors receiving current or updated informationregarding weather, traffic, construction, and/or road conditions viawireless communication, such as via wireless communication or datatransmission from another vehicle (vehicle-to-vehicle communication)(e.g., from another vehicle traveling ahead of the vehicle); from smartinfrastructure (infrastructure-to-vehicle communication) (e.g., fromsmart traffic lights, smart street signs, or smart tollbooths); and/orfrom mobile devices (pedestrian-to-vehicle communication).

The method may include adjusting or updating, at or via an insuranceprovider remote processor or server, a life, home, renters, and/orhealth insurance policy (or associated premium, rate, rewards or pointsprogram, and/or discount) based upon driver usage of autonomous orsemi-autonomous functionality or technology; an amount that the driveruses one or more different autonomous or semi-autonomous functionalitiesor technologies; and/or how well the specific driver uses, engages,and/or operates one or more autonomous or semi-autonomousfunctionalities or technologies.

G. Driving Score

In another aspect, a computer-implemented method of providing orenhancing vehicle operation safety may be provided. The method mayinclude (1) building a driver profile over time, via one or moreprocessors (such as one or more local or remote processors, e.g.,vehicle-mounted local processors or insurance provider remoteprocessors), the driving profile including driving behavior and/orcharacteristic data associated with a specific driver of a vehicle, thedriver behavior and/or characteristic data associated with drivingscores or ratings for different environmental or roads conditions, suchas different weather, traffic, construction, or road conditions; (2)identifying (or receiving data indicative of), via the one or moreprocessors, one or more current environmental or road conditions (orother unfavorable driving condition) through which a vehicle istraveling or approaching; (3) determining, via the one or moreprocessors, that the specific driver drives or operates the vehiclebetter than an autonomous or semi-autonomous functionality or technologyin the one or more current environmental or road conditions based uponanalysis or comparison of, via the one or more processors: (a) the oneor more current environmental or road conditions (or other unfavorabledriving condition); (b) the driving profile, and/or driving behaviorand/or characteristic data associated with the specific driver; and/or(c) a driving score or rating of the autonomous or semi-autonomousfunctionality or technology, such as a score or rating associated withindividual environmental or road conditions for the autonomous orsemi-autonomous functionality or technology. The method may include,when it is determined that the specific driver drives or operates thevehicle better than the autonomous or semi-autonomous functionality ortechnology in the one or more current environmental or road conditions,via the one or more processors: (i) preventing the specific driver fromturning on, switching to, or otherwise engaging, the autonomous orsemi-autonomous functionality or technology; (ii) alerting the specificdriver and then automatically dis-engaging the autonomous orsemi-autonomous functionality or technology, or otherwise transferringdriving responsibility back to the specific driver; and/or (iii) issuinga warning or recommendation to the specific driver to take control ofthe vehicle and/or manually dis-engage the autonomous or semi-autonomousfunctionality or technology to facilitate safer driving or vehicleoperation. The method may include additional, fewer, or alternateactions, including those discussed elsewhere herein.

The method may include updating or adjusting, via the one or moreprocessors, an insurance policy, premium, rate, rewards or pointsprogram, and/or discount based upon the driver accepting or followingthe recommendation (regarding vehicle driver (i.e., who should drive oroperate the vehicle—a person or the vehicle) or mode of operation), or apercentage of time that the driver follows recommendations provided.

Identifying (or receiving data indicative of), via the one or moreprocessors, a current environmental or road condition (or otherunfavorable driving condition) through which the vehicle is traveling,or approaching, may include the one or more processors receiving currentor updated information regarding weather, traffic, construction, and/orroad conditions via a wired or wireless communication network, such asover the internet and/or from third party or government websites.Identifying (or receiving data indicative of), via the one or moreprocessors, a current environmental or road condition (or otherunfavorable driving condition) through which the vehicle is traveling,or approaching, may also include the one or more processors receivingcurrent or updated information regarding weather, traffic, construction,and/or road conditions from one or more vehicle-mounted sensors orcameras that capture information regarding conditions external to,and/or in front of, the vehicle.

Additionally or alternatively, identifying (or receiving data indicativeof), via the one or more processors, a current environmental or roadcondition (or other unfavorable driving condition) through which thevehicle is traveling, or approaching, may include the one or moreprocessors receiving current or updated information regarding weather,traffic, construction, and/or road conditions via wirelesscommunication, such as via wireless communication or data transmissionfrom another vehicle (vehicle-to-vehicle communication)(e.g., fromanother vehicle traveling ahead of the vehicle or a train); from smartinfrastructure (infrastructure-to-vehicle communication) (e.g., fromsmart traffic lights, smart street signs, or smart tollbooths); and/orfrom mobile devices (pedestrian-to-vehicle communication).

The method may include adjusting or updating, at or via an insuranceprovider remote processor or server, a life, home, renters, and/orhealth insurance policy (or associated premium, rate, rewards or pointsprogram, and/or discount) based upon driver usage of autonomous orsemi-autonomous functionality or technology; an amount that the driveruses one or more different autonomous or semi-autonomous functionalitiesor technologies; and/or how well the specific driver uses, engages,and/or operates one or more autonomous or semi-autonomousfunctionalities or technologies.

Drowsy Driver

In one aspect, a computer-implemented method of enhancing vehicle safetymay be provided. The method may include (1) capturing or gathering, viaone or more processors (such as one or more local or remote processors,e.g., vehicle-mounted local processors or insurance provider remoteprocessors), driver characteristic data associated with driver acuity ofa driver of a vehicle (and/or including image or audio data); (2)comparing, via the one or more processors, the driver characteristicdata with a first baseline of acuity information of normal drivers, orwith a second baseline of acuity information for the driver collectedover time, the first or second baseline being stored in a memory unitaccessible by the one or more processors; (3) based upon the comparison,via the one or more processors, determining that the driver is drowsyand/or is otherwise associated with a higher than normal risk of vehicleaccident; and/or (4) in response, via the one or more processors,engaging autonomous or semi-autonomous functionality or technology (orself-driving functionality) of the vehicle, and/or recommending to thedriver to engage the autonomous or semi-autonomous functionality ortechnology (or self-driving functionality) of the vehicle to facilitateaccident prevention and/or safer driving or vehicle operation. Themethod may include additional, fewer, or alternate actions, includingthose discussed elsewhere herein.

For instance, the one or more processors may determine that the driveris drowsy based upon images of the driver, and facial recognitionsoftware techniques and/or analysis of eyes or eye behavior of thedriver, and/or body or head position or behavior of the driver. Themethod may include updating or adjusting, via the one or moreprocessors, an insurance policy, premium, rate, rewards or pointsprogram, and/or discount based upon the driver accepting or followingthe recommendation (regarding vehicle driver (such as either a human orvehicle driver) or mode of operation), or a percentage of time that thedriver follows recommendations provided.

Unsafe Driver

In another aspect, a computer-implemented method of enhancing vehicleoperation safety may be provided. The method may include (1) gatheringor collecting, at or via one or more processors (such as one or morelocal or remote processors, e.g., vehicle-mounted local processors orinsurance provider remote processors), driving behavior orcharacteristic data of a specific driver while the specific driver isdriving a vehicle, the data being generated or collected by one or morevehicle-mounted sensors, cameras, processors, and/or systems (and/orincluding image and/or audio data); (2) determining, at or via one ormore processors, that the driver is driving the vehicle in an unsafemanner based upon computer analysis of the driving behavior orcharacteristic data; and/or (3) automatically engaging, via one or moreprocessors, an autonomous or semi-autonomous functionality or technologyof a vehicle when it is determined, by the one or more processors, thatit is safer for the vehicle to operate with the autonomous orsemi-autonomous functionality or technology engaged based upon computeranalysis of the driving behavior or characteristic data and/or thedetermination that the driver is driving or operating the vehicle in anunsafe manner. The method may include additional, fewer, or alternateactions, including those discussed elsewhere herein.

For instance, the computer analysis of the driving behavior orcharacteristic data and/or the determination that the driver is drivingor operating the vehicle in an unsafe manner may be based upon, or mayinclude, a determination, via the one or more processors, that thevehicle is swerving; not staying in the correct lane; not staying on theroad; switching or crossing lanes improperly; not stopping at stop signsor traffic lights; not signaling correctly; traveling in the wrongdirection or lane; traveling on the wrong side of a two-lane road;traveling too slow for road conditions or a posted speed limit; and/ortraveling too fast for road conditions or the posted speed limit. Thedetermination that the driver is driving or operating the vehicle in anunsafe manner may be based upon a determination that the vehicle isbeing operated in an unsafe manner or not according to, or in accordancewith, driving laws or statutes, or posted speed limits.

Inattentive or Distracted Driver

In one aspect, a computer-implemented method of enhancing vehicle safetyor operation may be provided. The method may include (1) capturing orgathering, via one or more processors (such as one or more local orremote processors, e.g., vehicle-mounted local processors or insuranceprovider remote processors), driver characteristic or behavior dataassociated with driver attentiveness, or lack thereof, of a specificdriver of a vehicle, the driver characteristic or behavior dataincluding image or audio data associated with the specific driver and/oran interior of the vehicle; (2) comparing, via the one or moreprocessors, the driver characteristic or behavior data with a firstbaseline of attentiveness information of normal or average drivers, orwith a second baseline of attentiveness for the specific drivercollected over time, the first or second baseline being stored in amemory unit; (3) based upon the comparison, via the one or moreprocessors, determining that the specific driver is un-attentive,distracted, or is otherwise associated with a higher than normal risk ofvehicle accident; and/or (4) in response, via the one or moreprocessors, engaging autonomous or semi-autonomous functionality ortechnology (or self-driving functionality) of the vehicle, and/orrecommending to the specific driver to engage the autonomous orsemi-autonomous functionality or technology (or self-drivingfunctionality) of the vehicle to facilitate accident prevention and/orsafer driving or vehicle operation. The method may include additional,fewer, or alternate actions, including those discussed elsewhere herein.

For instance, the one or more processors may determine that the specificdriver is un-attentive or distracted based upon computer analysis ofimages of the specific driver, and/or the computer analysis of the imagedata may indicate that the driver is not looking forward, or otherwisenot looking in the direction of vehicle travel. The one or moreprocessors may determine that the specific driver is un-attentive ordistracted based upon computer analysis of images of the specificdriver, and/or the computer analysis of the image data may indicate thatthe specific driver is looking toward the passenger seat, looking down(such as texting), is looking into the back seat area of the vehicle,and/or not looking forward or in the direction of vehicle travel.

The one or more processors may determine that the specific driver isun-attentive or distracted based upon computer analysis of images of thespecific driver, and/or the computer analysis of the image data mayindicate that the specific driver is texting or talking on a smartphone. Additionally or alternatively, the one or more processors maydetermine that the specific driver is un-attentive or distracted basedupon computer analysis of images of the specific driver, and/or thecomputer analysis of the image data may indicate that the specificdriver is moving their arms or head in a manner abnormal for driving.

The one or more processors may determine that the specific driver isun-attentive or distracted based upon computer analysis of images of thespecific driver, and/or the computer analysis of the image data mayindicate an abnormal position for driving, or unsafe for drivingposition, of one or more hands of the specific driver or the head of thespecific driver. Additionally or alternatively, the one or moreprocessors may determine that the specific driver is un-attentive ordistracted based upon computer analysis of the audio data, and/or thecomputer analysis of the audio data may indicate abnormal noise, sounds,or voices within the interior of the vehicle.

The method may include updating or adjusting, via the one or moreprocessors, an insurance policy, premium, rate, rewards or pointsprogram, and/or discount based upon the specific driver accepting orfollowing the recommendation (regarding vehicle driver, such as eitherrecommending a human or vehicle driver, or mode of operation), or apercentage of time that the specific driver follows recommendationsprovided.

Prevent Autonomous Functionality Engagement During Inclement Weather

In one aspect, a computer-implemented method of enhancing vehicleoperation or safety may be provided. The method may include (1)determining, via one or more processors, that an autonomous orsemi-autonomous functionality or technology of a vehicle is notoperating correctly or optimally, or otherwise is unsafe for currentweather or road conditions; (2) generating, via the one or moreprocessors, a warning to a driver of the vehicle indicating that theautonomous or semi-autonomous functionality or technology is notoperating correctly or optimally, or otherwise is unsafe for currentweather or road conditions; and/or (3) preventing, via the one or moreprocessors, the driver of the vehicle from engaging or switching on theautonomous or semi-autonomous functionality or technology that is notoperating correctly or optimally, or otherwise is unsafe for currentweather or road conditions. The method may include additional, fewer, oralternate actions, including those discussed elsewhere herein.

For instance, the method may include (a) generating, via the one or moreprocessors, a wireless communication indicating that the autonomous orsemi-autonomous functionality or technology is not operating correctlyor optimally, or otherwise is unsafe for current weather or roadconditions; (b) transmitting, via the one or more processors, thewireless communication to an insurance provider remote processor orserver; and/or (c) adjusting or updating, at or via the insuranceprovider remote processor or server, an insurance policy, premium, rate,rewards or points program, and/or discount for the vehicle based uponthe autonomous or semi-autonomous functionality or technology notoperating correctly or optimally, or otherwise being unsafe for currentweather or road conditions.

The method may include (1) receiving, at or via the insurance providerremote processor or server, via wireless communication from a mobiledevice of an insured that the autonomous or semi-autonomousfunctionality or technology that was not operating correctly oroptimally was repaired and/or received maintenance, and/or is nowoperating correctly or optimally, or otherwise operating safely; and/or(2) adjusting or updating, at or via the insurance provider remoteprocessor or server, an insurance policy, premium, rate, rewards orpoints program, and/or discount for the vehicle based upon theautonomous or semi-autonomous functionality or technology operatingcorrectly or optimally.

Determining, via the one or more processors, that the autonomous orsemi-autonomous functionality or technology of a vehicle is notoperating correctly or optimally, or otherwise is unsafe for currentweather or road conditions may be based upon rain, snow, fog, and/orlimited visibility conditions. Additionally or alternatively,determining, via the one or more processors, that the autonomous orsemi-autonomous functionality or technology of a vehicle is notoperating correctly or optimally, or otherwise is unsafe for currentweather or road conditions may be based upon one or more vehicle-mountedsensors not operating correctly or being covered by snow, ice, salt,dirt, dust, mud, and/or new or touch-up paint.

Further, determining, via one or more processors, that the autonomous orsemi-autonomous functionality or technology of the vehicle is notoperating correctly or optimally, or otherwise is unsafe for currentweather or road conditions may be based upon recognizing an abnormal orunusual condition, such as one or more pedestrians or traffic policemanbeing identified or recognized within a vicinity of, or approaching, thevehicle. Additionally or alternatively, determining, via one or moreprocessors, that the autonomous or semi-autonomous functionality ortechnology of the vehicle is not operating correctly or optimally, orotherwise is unsafe for current weather or road conditions may be basedupon recognizing an abnormal condition, such as a traffic light beingidentified or recognized within a vicinity of, or approaching, thevehicle as not working or operating correctly.

Engage Autonomous Functionality in Bad Weather

In one aspect, a computer-implemented method of enhancing safe vehicleoperation may be provided. The method may include (1) determining, viaone or more processors (such as a vehicle mounted processor and/or aninsurance provider remote processor), that a current (or approaching)weather condition (such as rain, snow, ice, or hail) presents a hazardor potential hazard to a vehicle, the vehicle being equipped withautonomous or semi-autonomous functionality or technology; and/or (2) inresponse (or based upon the foregoing determination), via the one ormore processors, the vehicle may engage the autonomous orsemi-autonomous functionality or technology, or may recommend to thedriver to engage the autonomous or semi-autonomous functionality ortechnology, to facilitate safer vehicle operation, driving, or traveland/or accident prevention. The method may include additional, fewer, oralternate actions, including those discussed elsewhere herein.

For instance, the method may include updating or adjusting, via the oneor more processors or at an insurance provider remote processor orserver, an insurance policy, premium, rate, rewards or points program,and/or discount based upon the vehicle automatically engaging theautonomous or semi-autonomous functionality or technology when it isdetermined that the current (or approaching) weather condition (such asrain, snow, ice, or hail) presents the hazard or potential hazard to thevehicle. The method may further include adjusting or updating, at or viaan insurance provider remote processor or server, a life, home, renters,and/or health insurance policy (or associated premium, rate, rewards orpoints program, and/or discount) based upon driver usage of autonomousor semi-autonomous functionality or technology; an amount that thedriver uses one or more different autonomous or semi-autonomousfunctionalities or technologies; and/or how well the specific driveruses, engages, and/or operates one or more autonomous or semi-autonomousfunctionalities or technologies.

Exemplary Methods for Vehicle Operator Identification

FIG. 8 illustrates a flow diagram depicting an exemplary vehicleoperator identification method 800 that may be used to adjust aninsurance policy associated with the vehicle operator or vehicle 108.The exemplary method 800 may begin with receipt of a request to identifythe vehicle operator of the vehicle at block 802. At blocks 804-810, thevehicle operator may be identified by sensor data or receivedindications of identity, such as from a mobile device 110. Once theidentity of the vehicle operator has been determined (or cannot bedetermined), the method 800 may further determine whether the vehicleoperator is authorized to operate the vehicle 108 at block 812. If thevehicle operator is not authorized, an alert may be generated andvehicle operations may be limited at blocks 814-816. If the vehicleoperator is authorized, a vehicle operator profile associated with thevehicle operator may be obtained at block 818, and/or an insurancepolicy associated with the vehicle 108 or the vehicle operator may beidentified at block 820. During vehicle operation, operating data of thevehicle 108 may be received and used to adjust the vehicle operatorprofile and the insurance policy at blocks 822-826. When vehicleoperation has been determined to be complete at block 828, the method800 may terminate. Although the exemplary embodiment is described asprimarily performed by the on-board computer 114, the method 800 may beimplemented by the mobile device 110, the on-board computer 114, theserver 140, and/or a combination thereof.

Exemplary Methods for Monitoring Use by Vehicle Operators

FIG. 9 illustrates a flow diagram depicting an exemplary vehicleoperator use monitoring and evaluation method 900 that may be used todetermine skill or risk levels associated with a vehicle operator oradjust an insurance policy. The exemplary method 900 may begin withdetermining the identity of the vehicle operator at block 902. If avehicle operator profile can be found for the vehicle operator at block904, the vehicle operator profile may be accessed at block 912. If novehicle operator profile can be found for the vehicle operator at block904, a vehicle operator profile may be created based upon vehicleoperations and stored for future use at blocks 906-910. The newlycreated vehicle operator profile may be generated at block 908 withvehicle operating data from only a short time period or may include onlyinformation regarding configuration and/or settings of the autonomousoperation features, in which case operation of the vehicle may continueafter the vehicle operator profile is generated. If operation isdetermined to be ongoing at block 914, vehicle operation may bemonitored and the vehicle operator profile may be updated at blocks916-924. In some embodiments, the vehicle operator may be able to selectan option of a mode for vehicle operation. If such a mode selection isdetected at block 916, the settings of the autonomous operation featuresmay be adjusted at block 918. Vehicle operation may be monitored atblock 920 based upon received operating data, which may be used todetermine adjustments to the vehicle operator profile at block 922. Theadjustments may then be used to update the vehicle operator profile atblock 924. When operation is complete, the method 900 may determine riskor skill levels associated with the vehicle operator at blocks 926-928.These determined levels may be used at blocks 930-934 to generate areport or adjust an insurance policy. Although the exemplary embodimentis described as primarily performed by the on-board computer 114, themethod 900 may be implemented by the mobile device 110, the on-boardcomputer 114, the server 140, and/or a combination thereof.

The vehicle operator profile may include information regarding thevehicle operator, including an operating style of the vehicle operation.The operating style may include information regarding frequency withwhich the vehicle operator operates the vehicle manually, uses one ormore autonomous operation features, selects one or more settings for theautonomous operation features, and/or takes control from the autonomousoperation features under various conditions. The operating style mayfurther include information regarding observed control decisions made bythe vehicle operator, such as rate of acceleration, frequency of lanechanges, use of vehicle signaling devices, distances maintained fromother vehicles or pedestrians, and/or other aspects of vehicleoperation. For example, vehicle operator decisions regarding how long tostop at a stop sign or when to begin accelerating from such a stop inthe presence of other vehicles or pedestrians may be included in theoperating style. The vehicle operator profile may further includeinformation regarding vehicle operator skill levels, as described below.In some embodiments, the vehicle operator profile may include a riskprofile or information regarding one or more risk levels associated withoperation of the vehicle by the vehicle operator. Such risk levels maybe associated with particular configurations or settings of autonomousoperation features and/or particular conditions of the vehicleenvironment (e.g., time of day, traffic levels, weather, etc.).

In further embodiments, the vehicle operator profile may includeinformation regarding attentiveness of the vehicle operator while thevehicle is being autonomously operated. For example, some vehicleoperators may typically pay attention to road conditions while a vehicleis operating in a fully autonomous mode, while other vehicle operatorsmay typically engage in other activities. In some embodiments, thevehicle operator profile may include information regarding decisionsmade by the vehicle operator regarding actions that would result inadjustments to costs associated with an insurance policy (e.g.,accepting or rejecting recommendations to optimize autonomous operationfeature use to lower insurance costs).

The vehicle operator profile or vehicle operator behavior data mayindicate how well the specific vehicle operator drives in rain, snow,sleet, ice, heavy traffic, road construction, stop-and-go traffic,bumper-to-bumper traffic, country or rural traffic, and/or city ordowntown street traffic. The current environment (or condition) mayinclude or be rain, ice, snow, fog, heavy traffic, bumper-to-bumpertraffic, road construction, city traffic, country or rural traffic,and/or may be associated with a type of road, such as a two-lane orfour-lane highway, and/or downtown city street or other street havingseveral traffic lights.

The operating mode may include one or more settings or configurations ofautonomous operation features. For example, operating modes may includeadjustments to settings that cause the autonomous operation features tocontrol the vehicle 108 in a more or less aggressive manner with respectto speed, distance from other vehicles, distance from pedestrians, etc.As an example, the settings may cause the vehicle 108 to remain at leasta minimum distance from other vehicles (which may depend upon vehiclespeed or road conditions), and/or modes may set different minimumdistances. Examples of modes may include a city driving mode, a highwaydriving mode, a rush operation mode, a smooth operation mode, a cautiousmode, and/or a user-defined mode.

In some embodiments, an operating mode may be based upon the vehicleoperator profile. For example, the vehicle profile may includeinformation indicating an operating style of the vehicle operator basedupon observations of control commands by the vehicle operator, whichprofile information may be used to generate an operation mode thatmimics the style of the vehicle operator. Thus, if the vehicle operatortypically stops at stop signs for a particular length of time, theoperating style may mimic this length of time to provide an experiencethat seems normal or customary to the vehicle operator.

Exemplary Methods for Comparing Costs

FIG. 10 illustrates a flow diagram depicting an exemplary costcomparison method 1000 that may be used to compare costs associated withvehicles, some of which may include autonomous operation features. Theexemplary method 1000 may begin by receiving a command to generate acomparison report between two or more alternative transportation optionsfor an insurance customer or other user. The method 1000 may furtherreceive information regarding one or more vehicle operators may bereceived at block 1004 and/or information regarding a first vehicle anda second vehicle at block 1006. The first and second vehicles may differin autonomous operation features or other characteristics. Cost levelsassociated with obtaining, operating, and insuring the first vehicle andthe second vehicle may be determined at block 1008, and/or arecommendation based upon the costs may be determined at block 1010. Areport including the costs levels, recommendation, and/or relatedinformation may be generated at block 1012 and presented to theinsurance customer or other user at block 1014. Additionally, one ormore options may be presented along with the report at block 1016, suchas options to perform another comparison or present additionalinformation. If an option is selected at block 1018, the correspondingaction may be performed at block 1020. Although the exemplary embodimentis described as primarily performed by the server 140, the method 1000may be implemented by the mobile device 110, the on-board computer 114,the server 140, and/or a combination thereof.

Exemplary Methods for Updating Autonomous Operation Features

FIG. 11 illustrates a flow diagram depicting an exemplary autonomousoperation feature update method 1100 that may be used to identify,recommend, and/or install updates to autonomous operation features inappropriate autonomous or semi-autonomous vehicles. In some embodiments,the updates may include software version updates. The exemplary method1100 may begin with the receipt of an indication of an available updateto an autonomous operation feature at block 1102, which may include anupdate to a version of autonomous operation feature software. Aplurality of vehicles having the autonomous operation feature may beidentified at block 1104 based upon recorded features or communicationwith the plurality of vehicles. A change in one or more risk levelsassociated with the update may be determined for some or all of theidentified vehicles at block 1106, and/or a change in a cost associatedwith one or more of the plurality of vehicles may be determined at block1108. If the determined changes in risk levels or insurance costs meetcertain criteria for installing the update at block 1110, a notificationregarding the update may be presented to an insurance customer at block1112. The notification may further include information regarding costsassociated with the update. If an indication of acceptance of the updateis received at block 1114, the update may be installed at block 1116.Although the exemplary embodiment is described as primarily performed bythe server 140, the method 1100 may be implemented by the mobile device110, the on-board computer 114, the server 140, and/or a combinationthereof.

Exemplary Methods for Repair of an Autonomous Vehicle

FIG. 12 illustrates a flow diagram depicting an exemplary autonomousvehicle repair method 1200 that may be used to determine repairs neededas a result of damage to an autonomous or semi-autonomous vehicle. Theexemplary method 1200 may begin by receiving an indication of damage tothe vehicle 108 at block 1202 and/or receiving operating data associatedwith the vehicle 108 at block 1204. Based upon the operating data, thetype and extent of damage to the vehicle 108 may be determined at block1206, and/or repairs needed to fix the damage may be determined at block1208. Additionally, one or more expected costs (or ranges of costs) forthe repairs may be estimated at block 1210. An insurance policyassociated with the vehicle 108 may be identified, and/or a maximumpayment for the repairs may be determined at block 1212 based upon theestimated costs and the insurance policy. Information regarding theestimated cost or costs and the maximum payment under the insurancepolicy may be presented to an insurance customer at block 1214.Additionally, options associated with the repairs may be presented tothe insurance customer at block 1216, and/or a selection of one or moreoptions may be received at block 1218. An insurer or other party maycause a payment to be made at block 1220 to the insurance customer,beneficiary, or other relevant party based upon the estimated costs ofrepairing the damage and the selected option. Although the exemplaryembodiment is described as primarily performed by the server 140, themethod 1200 may be implemented by the mobile device 110, the on-boardcomputer 114, the server 140, and/or a combination thereof.

Exemplary Methods for Infrastructure Communications

FIG. 13 illustrates a flow diagram depicting an exemplary infrastructurecommunication method 1300 that may be used to detect and communicateinformation regarding infrastructure components to vehicles. Theexemplary method 1300 may begin with the infrastructure communicationdevice 124 receiving information regarding the infrastructure component126 from one or more sensors at block 1302. The information may be usedat block 1304 to determine a message regarding the infrastructurecomponent 126. In some embodiments, the message may be augmented atblock 1306 by information associated with a sponsor or other partyaffiliated with the infrastructure communication device 124. The messagemay then be encoded at block 1308 and transmitted at block 1310, whichmay cause the message to be presented to the vehicle operator of thevehicle 108 at block 1312. Although the exemplary embodiment describesone infrastructure communication device 124 communicating with onevehicle 108, it should be understood than any number of infrastructurecommunication devices 124 may communicate with any number of vehicles108.

Updating Insurance Policies

In one aspect, a computer-implemented method of updating an insurancepolicy may be provided. The method may include (a) gathering orreceiving, at or via one or more processors (such as either a localprocessor associated with a smart vehicle and/or a remote processor orserver associated with an insurance provider), data indicative of (1)vehicle usage, and/or (2) vehicle drivers for an insured vehicle; (b)analyzing the data, via the one or more processors, to determine (i) anamount and/or (ii) type of vehicle usage for each vehicle driver; (c)based upon the amount of vehicle usage for each vehicle driver and/orthe type of vehicle usage for each vehicle driver, via the one or moreprocessors, updating or adjusting an insurance policy (such as apremium, rate, rewards or points program, discount, etc.) for theinsured vehicle; (d) transmitting, under the direction or control of theone or more processors, the updated or adjusted insurance policy (orotherwise causing the updated or adjusted insurance policy to bepresented or displayed to the insured) to a mobile device of the insuredfor their review, modification, and/or approval; and/or (e) receiving,at or via the one or more processors, from the mobile device of theinsured (such as via wireless communication) an approval of the updatedor adjusted insurance policy of the insured to facilitate more accurateinsurance pricing and/or insurance cost savings. The method may includeadditional, fewer, or alternate actions, including those discussedelsewhere herein.

For instance, the amount of vehicle usage may include an amount of timeand/or miles that each individual vehicle driver drives the vehicle. Thetype of vehicle usage may include characterizing various periods ofdriving and/or trips as city driving; country driving; freeway orhighway driving city street driving; heavy traffic or congested trafficdriving; driving in good weather; driving in hazardous weather; rushhour driving; and/or time-of-day driving.

The vehicle drivers may be identified from mobile device signature; seatpressure sensors and weight; image recognition techniques performed uponimages of the driver; and/or biometric devices (such as heart beat orrate characteristics; voice print; and/or thumb or finger prints).

Biometric Device Data

In one aspect, a computer-implemented method of updating an insurancepolicy using biometric device data may be provided. The method mayinclude (a) gathering or receiving, at or via one or more processors(such as either a local processor associated with a smart vehicle and/ora remote processor or server associated with an insurance provider),data from a biometric device indicative of whom is driving an insuredvehicle; (b) gathering or receiving, at or via the one or moreprocessors, data indicative of vehicle usage for a single trip and/ordriving or driver behavior during the single trip; (c) updating oradjusting, at or via the one or more processors, an insurance policy(such as a premium, rate, rewards or points program, discount, etc.) forthe insured vehicle based upon (1) whom is driving the insured vehicle(and/or his or her driving profile or score), and/or (2) the dataindicative of vehicle usage for the single trip and/or the driving ordriver behavior exhibited during the single trip to facilitate moreaccurate risk assessment and/or cost savings to the insured. The methodmay include additional, fewer, or alternate actions, including thosediscussed elsewhere herein. For instance, the biometric device mayverify an identity of the driver based upon heartbeat, facialrecognition techniques, and/or mood.

In another aspect, a computer-implemented method of updating aninsurance policy may be provided. The method may include (1) gatheringor receiving, at or via one or more processors (such as either a localprocessor associated with a smart vehicle and/or a remote processor orserver associated with an insurance provider), data from a biometricdevice identifying a driver of an insured vehicle; (2) gathering orreceiving, at or via the one or more processors, data indicative ofdriving or driver behavior for the driver identified from the biometricdevice data; (3) generating, at or via the one or more processors, ausage-based insurance policy for the insured vehicle based upon (i) theidentity of the driver determined from the biometric device data, and/or(ii) the data indicative of driving or driver behavior exhibited by thedriver to facilitate more accurate risk assessment and/or provide costsavings to the insured. The method may include additional, fewer, oralternate actions, including those discussed elsewhere herein.

Software Versions

In one aspect, a computer-implemented method of updating an insurancepolicy may be provided. The method may include (1) gathering orreceiving, at or via one or more processors (such as either a localprocessor associated with a smart vehicle and/or a remote processor orserver associated with an insurance provider), data indicative of asoftware version installed on or in an insured vehicle that isassociated with an autonomous or semi-autonomous functionality; (2)determining, at or via the one or more processors, that the softwareversion is out of date or a (safer or less risky) new software versionexists and/or is available for download; (3) generating, at or via theone or more processors, a recommendation to an insured to update orupgrade to the new software version, and transmitting thatrecommendation under the direction or control of the one or moreprocessors to a mobile device or insured vehicle controller (such as viawireless communication or data transmission); (4) determining, at or viathe one or more processors, (or receiving an indication) that theinsured has updated or upgraded to the new software version associatedwith the autonomous or semi-autonomous functionality; and/or (5)updating or adjusting, at or via the one or more processors, aninsurance policy (such as a premium, rate, rewards or points program,discount, etc.) for the insured vehicle based upon the insured updatingor upgrading to the new software version associated with an autonomousor semi-autonomous functionality to facilitate providing cost savings tothe insured and/or enticing drivers to update vehicle software to mostrecent versions and/or versions that perform better. The method mayinclude additional, fewer, or alternate actions, including thosediscussed elsewhere herein.

Exemplary Autonomous Vehicle Insurance Risk and Price DeterminationMethods

Risk profiles or risk levels associated with one or more autonomousoperation features determined above may be further used to determinerisk categories or premiums for vehicle insurance policies coveringautonomous vehicles. In some embodiments or under some conditions, thevehicle 108 may be a fully autonomous vehicle operating without avehicle operator's input or presence. In other embodiments or underother conditions, the vehicle operator may control the vehicle 108 withor without the assistance of the vehicle's autonomous operationfeatures. For example, the vehicle may be fully autonomous only above aminimum speed threshold or may require the vehicle operator to controlthe vehicle during periods of heavy precipitation. Alternatively, theautonomous vehicle may perform all relevant control functions using theautonomous operation features under all ordinary operating conditions.In still further embodiments, the vehicle 108 may operate in either afully or a partially autonomous state, while receiving or transmittingautonomous communications.

Where the vehicle 108 operates only under fully autonomous control bythe autonomous operation features under ordinary operating conditions orwhere control by a vehicle operator may be disregarded for insurancerisk and price determination, the risk level or premium associated withan insurance policy covering the autonomous vehicle may be determinedbased upon the risks associated with the autonomous operation features,without reference to risks associated with the vehicle operator. Wherethe vehicle 108 may be operated manually under some conditions, the risklevel or premium associated with an insurance policy covering theautonomous vehicle may be based upon risks associated with both theautonomous operation features and the vehicle operator performing manualvehicle operation. Where the vehicle 108 may be operated with theassistance of autonomous communications features, the risk level orpremium associated with an insurance policy covering the autonomousvehicle may be determined based in part upon a determination of theexpected use of autonomous communication features by external sources inthe relevant environment of the vehicle 108 during operation of thevehicle 108.

Data Acquisition

In one aspect, the present embodiments may relate to data acquisition.Data may be gathered via devices employing wireless communicationtechnology, such as Bluetooth or other IEEE communication standards. Inone embodiment, a Bluetooth enabled smartphone or mobile device, and/oran in-dash smart and/or communications device may collect data. The dataassociated with the vehicle, and/or vehicle or driver performance, thatis gathered or collected at, or on, the vehicle may be wirelesslytransmitted to a remote processor or server, such as a remote processoror server associated with an insurance provider. The mobile device 110may receive the data from the on-board computer 114 or the sensors 120,and may transmit the received data to the server 140 via the network130, and the data may be stored in the database 146. In someembodiments, the transmitted data may include real-time sensor data, asummary of the sensor data, processed sensor data, operating data,environmental data, communication data, or a log such data.

Data may be generated by autonomous or semi-autonomous vehicles and/orvehicle mounted sensors (or smart sensors), and then collected byvehicle mounted equipment or processors, including Bluetooth devices,and/or an insurance provider remote processor or server. The datagathered may be used to analyze vehicle decision making. A processor maybe configured to generate data on what an autonomous or semi-autonomousvehicle would have done in a given situation had the driver not takenover manual control/driving of the vehicle or alternative controlactions not taken by the autonomous or semi-autonomous operationfeatures. This type of control decision data (related to vehicledecision making) may be useful with respect to analyzing hypotheticalsituations.

In one embodiment, an application, or other computer or processorinstructions, may interact with a vehicle to receive and/or retrievedata from autonomous or semi-autonomous processors and sensors. The dataretrieved may be related to radar, cameras, sensor output, computerinstructions or application output. Other data related to a smartvehicle controller, car navigation unit information (including routehistory information and typical routes taken), GPS unit information,odometer and/or speedometer information, and smart equipment data mayalso be gathered or collected. The application and/or other computerinstructions may be associated with an insurance provider remoteprocessor or server.

The control decision data may further include information regardingcontrol decisions generated by one or more autonomous operation featureswithin the vehicle. The operating data and control decision datagathered, collected, and/or acquired may facilitate remote evaluationand/or analysis of what the autonomous or semi-autonomous vehicle was“trying to do” (brake, slow, turn, accelerate, etc.) during operation,as well as what the vehicle actually did do. The data may revealdecisions, and the appropriateness thereof, made by the artificialintelligence or computer instructions associated with one or moreautonomous or semi-autonomous vehicle technologies, functionalities,systems, and/or pieces of equipment. The data may include informationrelated to what the vehicle would have done in a situation if the driverhad not taken over (beginning manual vehicle control). Such data mayinclude both the control actions taken by the vehicle and controlactions the autonomous or semi-autonomous operation features would havecaused the vehicle to take. Thus, in some embodiments, the controldecisions data may include information regarding control decisions notimplemented by the autonomous operation features to control the vehicle.This may occur when an autonomous operation feature generates a controldecision or associated control signal, but the control decision orsignal is prevented from controlling the vehicle because the autonomousfeature or function is disabled, the control decision is overridden bythe vehicle operator, the control signal would conflict with anothercontrol signal generated by another autonomous operation feature, a morepreferred control decision is generated, and/or an error occurs in theon-board computer 114 or the control system of the vehicle.

For example, a vehicle operator may disable or constrain the operationof some or all autonomous operation features, such as where the vehicleis operated manually or semi-autonomously. The disabled or constrainedautonomous operation features may, however, continue to receive sensordata and generate control decision data that is not implemented.Similarly, one or more autonomous operation features may generate morethan one control decision in a relevant period of time as alternativecontrol decisions. Some of these alternative control decisions may notbe selected by the autonomous operation feature or an autonomousoperation control system to control the vehicle. For example, suchalternative control decisions may be generated based upon different setsof sensor or communication data from different sensors 120 or include orexcluding autonomous communication data. As another example, thealternative control decisions may be generated faster than they can beimplemented by the control system of the vehicle, thus preventing allcontrol decisions from being implemented.

In addition to control decision data, other information regarding thevehicle, the vehicle environment, or vehicle operation may be collected,generated, transmitted, received, requested, stored, and/or recorded inconnection with the control decision data. Additional operating dataincluding sensor data from the sensors 120, autonomous communicationdata from the communication component 122 or the communication unit 220,location data, environmental data, time data, settings data,configuration data, and/or other relevant data may be associated withthe control decision data. In some embodiments, a database or log maystore the control decision data and associated information. In furtherembodiments, the entries in such log or database may include a timestampindicating the date, time, location, vehicle environment, vehiclecondition, autonomous operation feature settings, and/or autonomousoperation feature configuration information associated with each entry.Such data may facilitate evaluating the autonomous or semi-autonomoustechnology, functionality, system, and/or equipment in hypotheticalsituations and/or may be used to calculate risk, and in turn adjustinsurance policies, premiums, discounts, etc.

Autonomous Vehicle Insurance Policies

The disclosure herein relates to insurance policies for vehicles withautonomous operation features. Accordingly, as used herein, the term“vehicle” may refer to any of a number of motorized transportationdevices. A vehicle may be a car, truck, bus, train, boat, plane,motorcycle, snowmobile, other personal transport devices, etc. Also asused herein, an “autonomous operation feature” of a vehicle means ahardware or software component or system operating within the vehicle tocontrol an aspect of vehicle operation without direct input from avehicle operator once the autonomous operation feature is enabled orengaged. The term “autonomous vehicle” means a vehicle including atleast one autonomous operation feature. A “fully autonomous vehicle”means a vehicle with one or more autonomous operation features capableof operating the vehicle in the absence of or without operating inputfrom a vehicle operator.

Additionally, the term “insurance policy” or “vehicle insurance policy,”as used herein, generally refers to a contract between an insurer and aninsured. In exchange for payments from the insured, the insurer pays fordamages to the insured which are caused by covered perils, acts, orevents as specified by the language of the insurance policy. Thepayments from the insured are generally referred to as “premiums,” andtypically are paid by or on behalf of the insured upon purchase of theinsurance policy or over time at periodic intervals. Although insurancepolicy premiums are typically associated with an insurance policycovering a specified period of time, they may likewise be associatedwith other measures of a duration of an insurance policy, such as aspecified distance traveled or a specified number of trips. The amountof the damages payment is generally referred to as a “coverage amount”or a “face amount” of the insurance policy. An insurance policy mayremain (or have a status or state of) “in-force” while premium paymentsare made during the term or length of coverage of the policy asindicated in the policy. An insurance policy may “lapse” (or have astatus or state of “lapsed”), for example, when the parameters of theinsurance policy have expired, when premium payments are not being paid,when a cash value of a policy falls below an amount specified in thepolicy, or if the insured or the insurer cancels the policy.

The terms “insurer,” “insuring party,” and “insurance provider” are usedinterchangeably herein to generally refer to a party or entity (e.g., abusiness or other organizational entity) that provides insuranceproducts, e.g., by offering and issuing insurance policies. Typically,but not necessarily, an insurance provider may be an insurance company.The terms “insured,” “insured party,” “policyholder,” and “customer” areused interchangeably herein to refer to a person, party, or entity(e.g., a business or other organizational entity) that is covered by theinsurance policy, e.g., whose insured article or entity is covered bythe policy. Typically, a person or customer (or an agent of the personor customer) of an insurance provider fills out an application for aninsurance policy. In some cases, the data for an application may beautomatically determined or already associated with a potentialcustomer. The application may undergo underwriting to assess theeligibility of the party and/or desired insured article or entity to becovered by the insurance policy, and, in some cases, to determine anyspecific terms or conditions that are to be associated with theinsurance policy, e.g., amount of the premium, riders or exclusions,waivers, and the like. Upon approval by underwriting, acceptance of theapplicant to the terms or conditions, and payment of the initialpremium, the insurance policy may be in-force, (i.e., the policyholderis enrolled).

Although the exemplary embodiments discussed herein relate to automobileinsurance policies, it should be appreciated that an insurance providermay offer or provide one or more different types of insurance policies.Other types of insurance policies may include, for example, commercialautomobile insurance, inland marine and mobile property insurance, oceanmarine insurance, boat insurance, motorcycle insurance, farm vehicleinsurance, aircraft or aviation insurance, and other types of insuranceproducts.

Other Matters

Although the text herein sets forth a detailed description of numerousdifferent embodiments, it should be understood that the legal scope ofthe invention is defined by the words of the claims set forth at the endof this patent. The detailed description is to be construed as exemplaryonly and does not describe every possible embodiment, as describingevery possible embodiment would be impractical, if not impossible. Onecould implement numerous alternate embodiments, using either currenttechnology or technology developed after the filing date of this patent,which would still fall within the scope of the claims.

In one aspect, autonomous or semi-autonomous vehicle; telematics;interconnected home; mobile device; and/or other data, including thatdiscussed elsewhere herein, may be collected or received by an insuranceprovider remote server, such as via direct or indirect wirelesscommunication or data transmission, after a customer affirmativelyconsents or otherwise opts into an insurance discount, reward, or otherprogram. The insurance provider may then analyze the data received withthe customer's permission to provide benefits to the customer. As aresult, risk averse customers may receive insurance discounts or otherinsurance cost savings based upon data that reflects low risk behaviorand/or technology that mitigates or prevents risk to (i) insured assets,such as autonomous or semi-autonomous vehicles, and/or (ii) autonomousor semi-autonomous vehicle operators or passengers.

It should also be understood that, unless a term is expressly defined inthis patent using the sentence “As used herein, the term ‘_(——————)’ ishereby defined to mean . . . ” or a similar sentence, there is no intentto limit the meaning of that term, either expressly or by implication,beyond its plain or ordinary meaning, and such term should not beinterpreted to be limited in scope based upon any statement made in anysection of this patent (other than the language of the claims). To theextent that any term recited in the claims at the end of this disclosureis referred to in this disclosure in a manner consistent with a singlemeaning, that is done for sake of clarity only so as to not confuse thereader, and it is not intended that such claim term be limited, byimplication or otherwise, to that single meaning. Finally, unless aclaim element is defined by reciting the word “means” and a functionwithout the recital of any structure, it is not intended that the scopeof any claim element be interpreted based upon the application of 35U.S.C. § 112(f).

Throughout this specification, plural instances may implementcomponents, operations, or structures described as a single instance.Although individual operations of one or more methods are illustratedand described as separate operations, one or more of the individualoperations may be performed concurrently, and nothing requires that theoperations be performed in the order illustrated. Structures andfunctionality presented as separate components in example configurationsmay be implemented as a combined structure or component. Similarly,structures and functionality presented as a single component may beimplemented as separate components. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

Additionally, certain embodiments are described herein as includinglogic or a number of routines, subroutines, applications, orinstructions. These may constitute either software (code embodied on anon-transitory, tangible machine-readable medium) or hardware. Inhardware, the routines, etc., are tangible units capable of performingcertain operations and may be configured or arranged in a certainmanner. In example embodiments, one or more computer systems (e.g., astandalone, client or server computer system) or one or more hardwaremodules of a computer system (e.g., a processor or a group ofprocessors) may be configured by software (e.g., an application orapplication portion) as a hardware module that operates to performcertain operations as described herein.

In various embodiments, a hardware module may be implementedmechanically or electronically. For example, a hardware module maycomprise dedicated circuitry or logic that is permanently configured(e.g., as a special-purpose processor, such as a field programmable gatearray (FPGA) or an application-specific integrated circuit (ASIC) toperform certain operations. A hardware module may also compriseprogrammable logic or circuitry (e.g., as encompassed within ageneral-purpose processor or other programmable processor) that istemporarily configured by software to perform certain operations. Itwill be appreciated that the decision to implement a hardware modulemechanically, in dedicated and permanently configured circuitry, or intemporarily configured circuitry (e.g., configured by software) may bedriven by cost and time considerations.

Accordingly, the term “hardware” should be understood to encompass atangible entity, be that an entity that is physically constructed,permanently configured (e.g., hardwired), or temporarily configured(e.g., programmed) to operate in a certain manner or to perform certainoperations described herein. Considering embodiments in which hardwareis temporarily configured (e.g., programmed), the hardware need not beconfigured or instantiated at any one instance in time. Software mayaccordingly configure a processor, for example, to constitute aparticular hardware module at one instance of time and to constitute adifferent hardware module at a different instance of time. Hardwareelements can provide information to, and receive information from, otherhardware elements. Accordingly, the described hardware may be regardedas being communicatively coupled.

The various operations of example methods described herein may beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implemented modulesthat operate to perform one or more operations or functions. The modulesreferred to herein may, in some example embodiments, compriseprocessor-implemented modules. Similarly, the methods or routinesdescribed herein may be at least partially processor-implemented. Theperformance of certain of the operations may be distributed among theone or more processors, not only residing within a single machine, butdeployed across a number of machines. In some example embodiments, theprocessor or processors may be located in a single location (e.g.,within a home environment, an office environment or as a server farm),while in other embodiments the processors may be distributed across anumber of locations.

Unless specifically stated otherwise, discussions herein using wordssuch as “processing,” “computing,” “calculating,” “determining,”“presenting,” “displaying,” or the like may refer to actions orprocesses of a machine (e.g., a computer) that manipulates or transformsdata represented as physical (e.g., electronic, magnetic, or optical)quantities within one or more memories (e.g., volatile memory,non-volatile memory, or a combination thereof), registers, or othermachine components that receive, store, transmit, or displayinformation. As used herein any reference to “one embodiment” or “anembodiment” means that a particular element, feature, structure, orcharacteristic described in connection with the embodiment may beincluded in at least one embodiment. The appearances of the phrase “inone embodiment” in various places in the specification are notnecessarily all referring to the same embodiment. Some embodiments maybe described using the expression “coupled” and “connected” along withtheir derivatives. For example, some embodiments may be described usingthe term “coupled” to indicate that two or more elements are in directphysical or electrical contact. The term “coupled,” however, may alsomean that two or more elements are not in direct contact with eachother, but yet still co-operate or interact with each other. Theembodiments are not limited in this context.

As used herein, the terms “comprises,” “comprising,” “includes,”“including,” “has,” “having” or any other variation thereof, areintended to cover a non-exclusive inclusion. For example, a process,method, article, or apparatus that comprises a list of elements is notnecessarily limited to only those elements but may include otherelements not expressly listed or inherent to such process, method,article, or apparatus. Further, unless expressly stated to the contrary,“or” refers to an inclusive or and not to an exclusive or. In addition,use of the “a” or “an” are employed to describe elements and componentsof the embodiments herein. This is done merely for convenience and togive a general sense of the description. In this description, and theclaims that follow, the singular also includes the plural unless it isobvious that it is meant otherwise. This detailed description is to beconstrued as exemplary only and does not describe every possibleembodiment, as describing every possible embodiment would beimpractical, if not impossible. One could implement numerous alternateembodiments, using either current technology or technology developedafter the filing date of this application.

Upon reading this disclosure, those of skill in the art will appreciatestill additional alternative structural and functional designs forsystem and a method for assigning mobile device data to a vehiclethrough the disclosed principles herein. Thus, while particularembodiments and applications have been illustrated and described, it isto be understood that the disclosed embodiments are not limited to theprecise construction and components disclosed herein. Variousmodifications, changes and variations, which will be apparent to thoseskilled in the art, may be made in the arrangement, operation anddetails of the method and apparatus disclosed herein without departingfrom the spirit and scope defined in the appended claims.

The particular features, structures, or characteristics of any specificembodiment may be combined in any suitable manner and in any suitablecombination with one or more other embodiments, including the use ofselected features without corresponding use of other features. Inaddition, many modifications may be made to adapt a particularapplication, situation or material to the essential scope and spirit ofthe present invention. It is to be understood that other variations andmodifications of the embodiments of the present invention described andillustrated herein are possible in light of the teachings herein and areto be considered part of the spirit and scope of the present invention.

What is claimed is:
 1. A computer-implemented method for operating anautonomous or semi-autonomous vehicle, comprising, during operation ofthe autonomous or semi-autonomous vehicle: receiving, by one or moreprocessors, operating data regarding one or more autonomous operationfeatures operating the autonomous or semi-autonomous vehicle, whereinthe operating data includes data regarding a current operatingenvironment of the autonomous or semi-autonomous vehicle from one ormore sensors disposed within the autonomous or semi-autonomous vehicle;receiving, at one or more processors, a request to disable at least oneof the one or more autonomous operation features; determining, by one ormore processors, one or more autonomous operation risk levels associatedwith current operation of the autonomous or semi-autonomous vehicle inthe current operating environment by the one or more autonomousoperation features based upon the received operating data; determining,by one or more processors, one or more operator risk levels associatedwith operation of the autonomous or semi-autonomous vehicle in thecurrent operating environment by the vehicle operator based upon (i) thereceived operating data, and (ii) driving behavior settings for thevehicle operator, wherein the behavior settings include information thatis pre-determined and/or stored in a vehicle operator profile;calculating, by one or more processors, one or more relative risk levelsby comparing the one or more autonomous operation risk levels againstthe one or more operator risk levels; determining, by one or moreprocessors, whether to disable the at least one of the one or moreautonomous operation features based upon the one or more relative risklevels; and causing, by one or more processors, an indication of thedetermination regarding whether to disable the at least one of the oneor more autonomous operation features to be presented to the vehicleoperator.
 2. The computer-implemented method of claim 1, furthercomprising: receiving, by one or more processors, autonomouscommunication data from one or more external sources, whereindetermining whether to disable the at least one of the one or moreautonomous operation features is further based upon the receivedautonomous communication data.
 3. The computer-implemented method ofclaim 1, wherein determining whether to disable the at least one of theone or more autonomous operation features includes determining not todisable the at least one of the one or more autonomous operationfeatures.
 4. The computer-implemented method of claim 3, furthercomprising: causing, by one or more processors, an option to overridethe determination not to disable the at least one of the one or moreautonomous operation features to be presented to the vehicle operator;receiving, at one or more processors, a selection of the option tooverride the determination not to disable the at least one of the one ormore autonomous operation features; and causing, by one or moreprocessors, the at least one of the one or more autonomous operationfeatures to be disabled.
 5. The computer-implemented method of claim 3,further comprising: causing, by one or more processors, an option tooverride the determination not to disable the at least one of the one ormore autonomous operation features to be presented to the vehicleoperator; receiving, at one or more processors, a selection of theoption to override the determination not to disable the at least one ofthe one or more autonomous operation features; determining, by one ormore processors, one or more risk levels associated with disabling theat least one of the one or more autonomous operation features; andcausing, by one or more processors, the at least one of the one or moreautonomous operation features to be disabled only if the determined oneor more risk levels associated with disabling the at least one of theone or more autonomous operation features are below a criticalthreshold.
 6. The computer-implemented method of claim 3, furthercomprising: causing, by one or more processors, an option to overridethe determination not to disable the at least one of the one or moreautonomous operation features to be presented to the vehicle operator;receiving, at one or more processors, a selection of the option tooverride the determination not to disable the at least one of the one ormore autonomous operation features; and adjusting, by one or moreprocessors, one or more costs associated with an insurance policyassociated with the vehicle operator based upon the selection of theoption to override the determination not to disable the at least one ofthe one or more autonomous operation features.
 7. Thecomputer-implemented method of claim 6, wherein the one or more costsassociated with the insurance policy associated with the vehicleoperator is further based upon the determined one or more autonomousoperation risk levels and the determined one or more operator risklevels.
 8. The computer-implemented method of claim 1, furthercomprising: determining, by one or more processors, a preparedness levelof the vehicle operator to assume control of one or more functions ofoperating the autonomous or semi-autonomous vehicle controlled by the atleast one of the one or more autonomous operation features, whereindetermining whether to disable the at least one of the one or moreautonomous operation features further based upon the determinedpreparedness level of the vehicle operator.
 9. The computer-implementedmethod of claim 1, further comprising adjusting, by one or moreprocessors, one or more insurance policies based upon the determined oneor more autonomous operation risk levels and the determined one or moreoperator risk levels, wherein the one or more insurance policies includeat least one of: a vehicle insurance policy, a life insurance policy,home insurance policy, a rental insurance policy, a condominiuminsurance policy, a disability insurance policy, a business insurancepolicy, a health insurance policy, or a liability insurance policy. 10.The computer-implemented method of claim 1, wherein the operating dataincludes data regarding the vehicle environment, including one or moreof the following: traffic conditions, construction, road integrity, typeof road, geographical location, time of day, precipitation, visibility,light levels, wind, or other weather conditions.
 11. Thecomputer-implemented method of claim 1, further comprising: determining,by one or more processors, an identity of a vehicle operator; andreceiving, at one or more processors, the vehicle operator profileassociated with the vehicle operator, wherein a default vehicle operatorprofile is received as the vehicle operator profile when the vehicleoperator cannot be identified as a known vehicle operator.
 12. Acomputer system for operating an autonomous or semi-autonomous vehicle,comprising: one or more processors; one or more sensors disposed withinthe autonomous or semi-autonomous vehicle and communicatively connectedto the one or more processors; and a program memory coupled to the oneor more processors and storing executable instructions that whenexecuted by the one or more processors cause the computer system to,during operation of the autonomous or semi-autonomous vehicle: receiveoperating data regarding one or more autonomous operation featuresoperating the autonomous or semi-autonomous vehicle, wherein theoperating data includes data regarding a current operating environmentof the autonomous or semi-autonomous vehicle from the one or moresensors disposed within the autonomous or semi-autonomous vehicle;receive a request to disable at least one of the one or more autonomousoperation features; determine one or more autonomous operation risklevels associated with current operation of the autonomous orsemi-autonomous vehicle in the current operating environment by the oneor more autonomous operation features based upon the received operatingdata; determine one or more operator risk levels associated withoperation of the autonomous or semi-autonomous in the current operatingenvironment vehicle by the vehicle operator based upon (i) the receivedoperating data, and (ii) driving behavior settings for the vehicleoperator, wherein the behavior settings include information that ispre-determined and/or stored in a vehicle operator profile; calculateone or more relative risk levels by comparing the one or more autonomousoperation risk levels against the one or more operator risk levels;determine whether to disable the at least one of the one or moreautonomous operation features based upon the one or more relative risklevels; and cause an indication of the determination regarding whetherto disable the at least one of the one or more autonomous operationfeatures to be presented to the vehicle operator.
 13. The computersystem of claim 12, wherein the program memory further includesexecutable instructions that cause the computer system, when thecomputer system determines not to disable the at least one of the one ormore autonomous operation features, to: cause an option to override thedetermination not to disable the at least one of the one or moreautonomous operation features to be presented to the vehicle operator;receive a selection of the option to override the determination not todisable the at least one of the one or more autonomous operationfeatures; and cause the at least one of the one or more autonomousoperation features to be disabled.
 14. The computer system of claim 12,wherein the program memory further includes executable instructions thatcause the computer system, when the computer system determines not todisable the at least one of the one or more autonomous operationfeatures, to: cause an option to override the determination not todisable the at least one of the one or more autonomous operationfeatures to be presented to the vehicle operator; receive a selection ofthe option to override the determination not to disable the at least oneof the one or more autonomous operation features; determine one or morerisk levels associated with disabling the at least one of the one ormore autonomous operation features; and cause the at least one of theone or more autonomous operation features to be disabled only if thedetermined one or more risk levels associated with disabling the atleast one of the one or more autonomous operation features are below acritical threshold.
 15. The computer system of claim 12, wherein theprogram memory further includes executable instructions that cause thecomputer system, when the computer system determines not to disable theat least one of the one or more autonomous operation features, to: causean option to override the determination not to disable the at least oneof the one or more autonomous operation features to be presented to thevehicle operator; receive a selection of the option to override thedetermination not to disable the at least one of the one or moreautonomous operation features; and adjust one or more costs associatedwith an insurance policy associated with the vehicle operator based uponthe selection of the option to override the determination not to disablethe at least one of the one or more autonomous operation features,wherein the one or more costs associated with the insurance policyassociated with the vehicle operator is further based upon thedetermined one or more autonomous operation risk levels and thedetermined one or more operator risk levels.
 16. A tangible,non-transitory computer-readable medium storing executable instructionsfor operating an autonomous or semi-autonomous vehicle that, whenexecuted by at least one processor of a computer system, cause thecomputer system to, during operation of the autonomous orsemi-autonomous vehicle: receive operating data regarding one or moreautonomous operation features operating the autonomous orsemi-autonomous vehicle, wherein the operating data includes dataregarding a current operating environment of the autonomous orsemi-autonomous vehicle from one or more sensors disposed within theautonomous or semi-autonomous vehicle; receive a request to disable atleast one of the one or more autonomous operation features; determineone or more autonomous operation risk levels associated with currentoperation of the autonomous or semi-autonomous vehicle in the currentoperating environment by the one or more autonomous operation featuresbased upon the received operating data; determine one or more operatorrisk levels associated with operation of the autonomous orsemi-autonomous vehicle in the current operating environment by thevehicle operator based upon (i) the received operating data, and (ii)driving behavior settings for the vehicle operator, wherein the behaviorsettings include information that is pre-determined and/or stored in avehicle operator profile; calculate one or more relative risk levels bycomparing the one or more autonomous operation risk levels against theone or more operator risk levels; determine whether to disable the atleast one of the one or more autonomous operation features based uponthe one or more relative risk levels; and cause an indication of thedetermination regarding whether to disable the at least one of the oneor more autonomous operation features to be presented to the vehicleoperator.
 17. The tangible, non-transitory computer-readable medium ofclaim 16, further storing executable instructions that cause thecomputer system, when the computer system determines not to disable theat least one of the one or more autonomous operation features, to: causean option to override the determination not to disable the at least oneof the one or more autonomous operation features to be presented to thevehicle operator; receive a selection of the option to override thedetermination not to disable the at least one of the one or moreautonomous operation features; and cause the at least one of the one ormore autonomous operation features to be disabled.
 18. The tangible,non-transitory computer-readable medium of claim 16, further storingexecutable instructions that cause the computer system, when thecomputer system determines not to disable the at least one of the one ormore autonomous operation features, to: cause an option to override thedetermination not to disable the at least one of the one or moreautonomous operation features to be presented to the vehicle operator;receive a selection of the option to override the determination not todisable the at least one of the one or more autonomous operationfeatures; determine one or more risk levels associated with disablingthe at least one of the one or more autonomous operation features; andcause the at least one of the one or more autonomous operation featuresto be disabled only if the determined one or more risk levels associatedwith disabling the at least one of the one or more autonomous operationfeatures are below a critical threshold.
 19. The tangible,non-transitory computer-readable medium of claim 16, further storingexecutable instructions that cause the computer system, when thecomputer system determines not to disable the at least one of the one ormore autonomous operation features, to: cause an option to override thedetermination not to disable the at least one of the one or moreautonomous operation features to be presented to the vehicle operator;receive a selection of the option to override the determination not todisable the at least one of the one or more autonomous operationfeatures; and adjust one or more costs associated with an insurancepolicy associated with the vehicle operator based upon the selection ofthe option to override the determination not to disable the at least oneof the one or more autonomous operation features, wherein the one ormore costs associated with the insurance policy associated with thevehicle operator is further based upon the determined one or moreautonomous operation risk levels and the determined one or more operatorrisk levels.
 20. The tangible, non-transitory computer-readable mediumof claim 16, further storing executable instructions that cause thecomputer system to: adjust one or more insurance policies based upon thedetermined one or more autonomous operation risk levels and thedetermined one or more operator risk levels, wherein the one or moreinsurance policies include at least one of: a vehicle insurance policy,a life insurance policy, home insurance policy, a rental insurancepolicy, a condominium insurance policy, a disability insurance policy, abusiness insurance policy, a health insurance policy, or a liabilityinsurance policy.